{"id":"W7107950087","doi":"10.60825/zcwf-6n63","title":"Developing a gillnet based abundance-at-age index for 4RSw Atlantic herring","year":2025,"lang":"en","type":"report","venue":"Fisheries and Oceans Canada / Pêches et Océans Canada - Publications","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada","funders":"","keywords":"Index (typography); Herring; Stock (firearms); Stock assessment; Index method; Fish stock","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.00216816,0.0006167005,0.0003114981,0.002313585,0.0003435687,0.0009712596,0.0005027741,0.0002676201,0.001050566],"category_scores_gemma":[0.00343963,0.0002857402,0.0003882918,0.001331915,0.0001325274,0.001170521,0.0006939258,0.0003856373,0.0007791519],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002256533,"about_ca_system_score_gemma":0.003122229,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1114626,"about_ca_topic_score_gemma":0.2278571,"domain_scores_codex":[0.9990984,0.0001157345,0.00009899646,0.0001526373,0.0004645633,0.0000696949],"domain_scores_gemma":[0.9983653,0.0001355026,0.0003079812,0.00009006481,0.001016326,0.0000847324],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007346504,0.0001129798,0.7651815,0.0001045706,0.0001130494,0.0000428968,0.0001526614,0.0213709,0.006590648,0.001447031,0.00451437,0.2002958],"study_design_scores_gemma":[0.00002529464,0.0004801497,0.7040585,0.00009648203,0.0001060308,0.0001319377,0.0006132192,0.2590479,0.0128119,0.001299032,0.02123281,0.00009677831],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.7533166,0.0003399016,0.2108629,0.0003655222,0.0000879416,0.001221769,0.01607687,0.001128305,0.01660023],"genre_scores_gemma":[0.5713462,0.0004782613,0.3923761,0.00009353599,0.00003787231,0.0006426112,0.02542941,0.0001201571,0.009475813],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.8885374,"threshold_uncertainty_score":0.2216277,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04619698195408136,"score_gpt":0.2693352818286622,"score_spread":0.2231382998745809,"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."}}