{"id":"W2610838835","doi":"10.1101/117556","title":"Methods to Reduce Sea Turtle Interactions in the Atlantic Canadian Pelagic Long Line Fleet","year":2017,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Turtle Biology and Conservation","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Francis Xavier University","funders":"","keywords":"Fishery; Swordfish; Fishing; Sea turtle; Pelagic zone; Foraging; Turtle (robot); Geography; Tuna; Fisheries management; Gelatinous zooplankton; Oceanography; Ecology; Biology; Fish <Actinopterygii>","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005383044,0.0005459009,0.0002753545,0.0009524304,0.0007566495,0.0004734324,0.0008393951,0.00023457,0.004617826],"category_scores_gemma":[0.001392479,0.000106733,0.0003264924,0.0003804951,0.0002275696,0.0001830085,0.0005311916,0.0003165739,0.0005472132],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001499686,"about_ca_system_score_gemma":0.00317849,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3060221,"about_ca_topic_score_gemma":0.5871266,"domain_scores_codex":[0.9996761,0.00003729728,0.00001152941,0.00005776815,0.0001594168,0.00005780623],"domain_scores_gemma":[0.999431,0.00005566066,0.0001168484,0.00004318286,0.0002654047,0.00008779579],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00101287,0.00154959,0.0839916,0.0007609369,0.0003597244,0.0002988703,0.0010653,0.01492261,0.1165291,0.00154796,0.01358022,0.7643812],"study_design_scores_gemma":[0.0004880572,0.004361305,0.7276518,0.0006096191,0.001121185,0.0004639538,0.005267471,0.07681782,0.07885742,0.002043582,0.1021204,0.0001975101],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8883813,0.002288429,0.08380364,0.001484032,0.0002593937,0.001730288,0.001376259,0.001141078,0.01953553],"genre_scores_gemma":[0.915485,0.0009483287,0.06183961,0.0005559036,0.00003447622,0.0006915169,0.0009916027,0.0001319073,0.01932168],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6939779,"threshold_uncertainty_score":0.6084818,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03110935201358743,"score_gpt":0.2945791489386835,"score_spread":0.263469796925096,"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."}}