{"id":"W7133282177","doi":"","title":"Science response: 2021 index for winter flounder","year":2022,"lang":"en","type":"other","venue":"Federal Open Science Repository of Canada / Le Dépôt fédéral de science ouverte du Canada","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fisheries and Oceans Canada","keywords":"Stock (firearms); Stock assessment; Fishing; Winter flounder; Fisheries management","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.003196798,0.0008092623,0.0005395547,0.002475672,0.001676339,0.00299475,0.001984313,0.004045804,0.1012399],"category_scores_gemma":[0.009043257,0.0003288174,0.0006180253,0.002105133,0.0004931394,0.001037268,0.002019547,0.002208231,0.08781393],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005928697,"about_ca_system_score_gemma":0.02755093,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.230902,"about_ca_topic_score_gemma":0.2956784,"domain_scores_codex":[0.9958199,0.0002413167,0.0001652041,0.0002062599,0.003004822,0.0005624244],"domain_scores_gemma":[0.9779424,0.0004374233,0.000566093,0.0004459503,0.01909148,0.001516613],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.00002234166,0.00001229854,0.0004370805,0.00007375122,0.000002357611,0.00001869555,0.00001502239,0.00003492763,0.0001525212,0.0002361016,0.9931774,0.00581744],"study_design_scores_gemma":[0.000007480253,0.00001292202,0.001843999,0.00003711913,0.000002895353,0.000006180759,0.00006176414,0.00003283449,0.0001327939,0.0000720353,0.997784,0.00000606714],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.004324546,0.002064131,0.001709297,0.1145844,0.03335398,0.002531905,0.2346471,0.0043603,0.6024244],"genre_scores_gemma":[0.0159326,0.002808244,0.004328475,0.0574717,0.005073122,0.001667638,0.1461784,0.001116305,0.7654235],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.769098,"threshold_uncertainty_score":0.459116,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009880590379202409,"score_gpt":0.2505312996856212,"score_spread":0.2406507093064187,"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."}}