{"id":"W2320412904","doi":"","title":"Aggregated Sablefish Longline Catch and Effort Grid 1996-2004","year":2006,"lang":"en","type":"article","venue":"downloadable data","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Groundfish; Fishing; Fishery; Grid; Stock (firearms); Geography; Environmental science; Computer science; Fisheries management","routes":{"ca_aff":false,"ca_fund":false,"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":[0.00050084,0.0004964047,0.0004391835,0.002760694,0.0002100038,0.000501977,0.0006471376,0.0002188962,0.007702919],"category_scores_gemma":[0.002305571,0.0002386566,0.0003072304,0.004030454,0.0000717685,0.0003331485,0.0005292168,0.0003773481,0.005119618],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001168203,"about_ca_system_score_gemma":0.00103154,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0939672,"about_ca_topic_score_gemma":0.1156757,"domain_scores_codex":[0.9993824,0.00006168276,0.00009496267,0.0001629398,0.0002365027,0.00006154743],"domain_scores_gemma":[0.9982961,0.0001184454,0.0004141169,0.0002248776,0.0008353457,0.000111147],"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":[0.0007576633,0.0001668297,0.3656477,0.0005950473,0.0003952183,0.0002142284,0.0003387688,0.01117802,0.001108397,0.0009828564,0.5790873,0.03952792],"study_design_scores_gemma":[0.00008105535,0.00008118517,0.8334228,0.00005970979,0.0000475722,0.0001084508,0.0002667861,0.004212149,0.0007040838,0.0002404421,0.1607497,0.00002612296],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.05142161,0.00005366495,0.0003935185,0.00006569145,0.00004487965,0.00005858296,0.9439276,0.0002599914,0.003774496],"genre_scores_gemma":[0.04989579,0.00006639559,0.001043078,0.00003184778,0.0000139609,0.0001713326,0.9437475,0.00004123245,0.004988834],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0939672,"threshold_uncertainty_score":0.1868405,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01597203698252217,"score_gpt":0.2376291958323429,"score_spread":0.2216571588498208,"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."}}