{"id":"W3131575474","doi":"10.3389/fmars.2021.606932","title":"Minding the Data-Gap Trap: Exploring Dynamics of Abundant Dolphin Populations Under Uncertainty","year":2021,"lang":"en","type":"article","venue":"Frontiers in Marine Science","topic":"Marine animal studies overview","field":"Environmental Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Environment Research Council; Sight Research UK; McLean Foundation","keywords":"Delphinus delphis; Bycatch; Fishery; Marine mammal; Population; Marine ecosystem; Bottlenose dolphin; Geography; Apex predator; Biology; Ecology; Ecosystem; Fishing; Demography","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001614726,0.0002578549,0.0002283743,0.0005525026,0.0003025067,0.0006693728,0.0007274976,0.0004669872,0.0005740788],"category_scores_gemma":[0.005103037,0.000219945,0.000316312,0.0003683371,0.0003700494,0.001047323,0.0006638115,0.0004286681,0.00004615551],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003676665,"about_ca_system_score_gemma":0.0004120761,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01053269,"about_ca_topic_score_gemma":0.01073641,"domain_scores_codex":[0.9997533,0.0001182608,0.000009245213,0.00006268443,0.000025117,0.00003137264],"domain_scores_gemma":[0.9978533,0.001547803,0.0003057134,0.0000891127,0.00009981386,0.0001041793],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001929257,0.0001076177,0.6475781,0.00006576504,0.0001811253,0.000321516,0.0007265983,0.3200866,0.002440824,0.002944293,0.0003761698,0.02497864],"study_design_scores_gemma":[0.00001076849,0.0001548864,0.06163523,0.00001173249,0.00002745412,0.0001074185,0.000620889,0.933876,0.0006000824,0.002649879,0.0002875544,0.0000181417],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9897923,0.00002950762,0.009487765,0.00005096121,0.000002074142,0.00001265591,0.0002051627,0.00002327931,0.000396111],"genre_scores_gemma":[0.995899,0.00001532013,0.003804321,0.00001007696,0.000001583136,0.00001086962,0.000162235,0.000003382304,0.00009318862],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01053269,"threshold_uncertainty_score":0.02094275,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1054872561813525,"score_gpt":0.2953849310305149,"score_spread":0.1898976748491624,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}