Choice of Filters

Filters This is CPOD.exe v2.050: Clicks shown are those that: pass all the filters and are within any TIME SELECTION that is set. very useful! train quality class species from KERNO species from KERNO species from encounter classifier trains clicks marked clicks / clicks with waveforms (F-POD)

Click filters: an example: How to find VEMCO fish tags Using the click filters (not the train filters): Set a long minimum click duration - say 30 cycles Set a frequency range corresponding to VEMCO fish tags - say minimum 69kHz, max 71kHz. Set a minimum number of clicks per screen - say 4 clicks Set the skip file to file 1 - this slot will normally show the CP1 or FP1 file. Use, say, 10ms time display resolution and the Duration view (F11) Use F1 to move from screen to screen Use F4 to remove and restore the filter so you can validate the identification on each screen. Satisfy yourself that the filter is working. Go to the Export page to export minutes with VEMCO tags heard.

} } } } true positives false positives Sensitivity v specificity – what is the right level? } } doubtful quality low quality This is a ‘ROC curve’ = receiver operating characteristic It’s different in different environments. true positives } moderate quality Start with tough criteria and no detections. As you make your detection criteria weaker you move along the red line and you get more detections … and more and more errors. } high quality false positives Hi + Mod is the standard because Low Q trains are commonly generated by adverse conditions - noise

} } } } true positives false positives In a noisier place: doubtful quality true positives low quality } moderate quality } high quality false positives

Encounter classifiers take information from a sequence of trains with no gap longer than n minutes. this move to a higher level gives more information on the train source. GENENC - a 'generalised encounter classifier' detects more dolphin trains, and usually reduces mis-identification of dolphins as NBHF species. HEL1 - developed for porpoise detection in Baltic Sea data at the Hel Marine Station in Poland. It assumes there are no dolphins.

Encounter classifiers this can be used to exclude VEMCO fish tags Encounter classifiers need the CP3 or FP3 file to exist run very quickly.

Standard filtering KERNO or GENENC. Hi + Mod Quality trains

the end useDPM, Hi + Mod quality trains