{"id":"W4236922525","doi":"10.18331/sfs","title":"Survey in Fisheries Sciences","year":2023,"lang":"en","type":"paratext","venue":"Journal of Survey in Fisheries Sciences","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Fishery; Fisheries science; Geography; Data science; Fisheries management; Fishing; Computer science; Biology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.02526492,0.0005767543,0.001303499,0.001014978,0.0005063097,0.0009359671,0.003621756,0.0004446118,0.02932049],"category_scores_gemma":[0.003831525,0.0004622801,0.0001995897,0.007427324,0.006375749,0.002055632,0.001366139,0.001536465,0.001226095],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004917063,"about_ca_system_score_gemma":0.0009481767,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.07277475,"about_ca_topic_score_gemma":0.2017621,"domain_scores_codex":[0.9904893,0.002362749,0.001876509,0.0009642068,0.00291274,0.001394472],"domain_scores_gemma":[0.995439,0.00270854,0.001035174,0.0004007793,0.0001437195,0.0002728188],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007995679,0.0000737441,0.6834391,0.00002850669,0.000009597908,0.00006426847,0.0002551958,0.0004485197,0.000007643156,0.00000130218,0.3132951,0.002297057],"study_design_scores_gemma":[0.0003326093,0.0007172864,0.8763901,0.0001141546,0.000003666617,0.00002441182,0.0003963438,0.00006310331,0.00001721117,0.0001409462,0.1212793,0.0005209138],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.4616015,0.0004541645,0.0000146676,0.001590359,0.00561111,0.000494034,0.000324134,0.00002247528,0.5298876],"genre_scores_gemma":[0.5513888,0.02299536,0.00176824,0.001077775,0.001236661,0.0001217164,0.0003153009,0.0003014416,0.4207947],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.192951,"threshold_uncertainty_score":0.9997829,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2615683083049204,"score_gpt":0.3313572391157381,"score_spread":0.06978893081081766,"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."}}