{"id":"W6904972729","doi":"10.14288/1.0007701","title":"Dr. E. Graham Bligh, Department of Fisheries Canada","year":2002,"lang":"en","type":"other","venue":"Open Collections","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Fishing; Government (linguistics); Work (physics); Fisheries management; Fisheries Research","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006817848,0.0006581769,0.0005198331,0.001964692,0.003410021,0.002806881,0.001072264,0.001199263,0.5203975],"category_scores_gemma":[0.001297098,0.0004522025,0.0002674458,0.001974861,0.0006326492,0.001160116,0.001159568,0.001526788,0.284811],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004268877,"about_ca_system_score_gemma":0.0102957,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5416364,"about_ca_topic_score_gemma":0.8235313,"domain_scores_codex":[0.9993802,0.00002017278,0.00001665656,0.0001008637,0.0003747825,0.0001072315],"domain_scores_gemma":[0.9977797,0.00006350721,0.00004240979,0.00005655639,0.001542226,0.0005156179],"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":[0.00002694992,0.00001404643,0.0006928775,0.00004709932,0.000001350756,0.00004736318,0.00005351664,0.00002915424,0.0002161896,0.0007465069,0.9547775,0.04334742],"study_design_scores_gemma":[0.000005367885,0.000007988323,0.002377396,0.00004788717,0.000002409049,0.00006165323,0.000153252,0.00005358436,0.0002008089,0.0001267154,0.9969549,0.000008034754],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00287015,0.003947438,0.0009915226,0.009811783,0.001747034,0.0002310647,0.01420332,0.001501785,0.9646958],"genre_scores_gemma":[0.002238697,0.001147053,0.0003389945,0.0002911937,0.00003490436,0.000009849208,0.001437706,0.000132698,0.994369],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.5203975,"threshold_uncertainty_score":0.922126,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02211669972679224,"score_gpt":0.2413954820250273,"score_spread":0.2192787822982351,"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."}}