{"id":"W4416659345","doi":"10.1079/9781836990888.0001","title":"Introduction","year":2025,"lang":"en","type":"book-chapter","venue":"CABI eBooks","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Saint Mary's University","funders":"","keywords":"IUCN Red List; Biodiversity; Fisheries management; Biodiversity conservation; Collateral damage; Fishing","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0004869384,0.0008366853,0.0004854461,0.001194621,0.002158476,0.005394747,0.001475203,0.002253646,0.3089144],"category_scores_gemma":[0.001326319,0.0002695691,0.0004213228,0.001443276,0.00146659,0.004021939,0.002571933,0.002345094,0.1765602],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002086621,"about_ca_system_score_gemma":0.001807834,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003468404,"about_ca_topic_score_gemma":0.005805143,"domain_scores_codex":[0.9993819,0.00007326137,0.00002661049,0.0001741992,0.000275453,0.00006864648],"domain_scores_gemma":[0.9995576,0.00009052037,0.00002215086,0.00006096342,0.0001905857,0.00007821992],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002475011,0.00003187907,0.000136483,0.0002521619,0.000002374395,0.0001320614,0.0008326769,0.0001109318,0.0003158572,0.1345206,0.6990602,0.1645799],"study_design_scores_gemma":[6.625832e-7,0.00000331969,0.00003882391,0.00006368331,4.031668e-7,0.00006487373,0.00005344272,0.000009449724,0.00003283264,0.002789802,0.9969413,0.000001403928],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.000536269,0.008237585,0.002129236,0.003731488,0.00388095,0.00005701668,0.0006414597,0.0002806427,0.9805054],"genre_scores_gemma":[0.002969738,0.003862065,0.001129238,0.001605299,0.0006407753,0.00003592098,0.0005022424,0.0001336271,0.9891211],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.6910856,"threshold_uncertainty_score":0.9857497,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01079400931202683,"score_gpt":0.2150356972364189,"score_spread":0.204241687924392,"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."}}