{"id":"W6938954872","doi":"10.6068/dp14ba7fef1ac53","title":"Trend 1997 - 2012. Statistics Canada. CANSIM: Agriculture - Livestock and Aquaculture | Country: Canada | Table: Aquaculture economic statistics, value-added account | Variable: Fish, dried, smoked or in brine | Units: $CAD x 1,000, 1997-2012. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-007.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Agriculture; Livestock; Economic statistics; Aquaculture; Census; Official statistics; Statistical analysis; Social statistics","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":[0.002132679,0.00244514,0.002667892,0.009199037,0.003229938,0.005091614,0.004803293,0.001565026,0.115706],"category_scores_gemma":[0.01780019,0.001952166,0.002028601,0.04502229,0.0006877505,0.002809958,0.002213593,0.003068323,0.06579773],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06530274,"about_ca_system_score_gemma":0.1662574,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9955205,"about_ca_topic_score_gemma":0.9935623,"domain_scores_codex":[0.9951215,0.0002840598,0.0004908227,0.0005658279,0.002431467,0.001106191],"domain_scores_gemma":[0.9616794,0.001256304,0.001099631,0.0009084461,0.03331909,0.001737152],"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":[0.00001844305,0.000005683296,0.000843241,0.0002256284,0.00001694461,0.00000617156,0.00001792577,0.00009884946,0.000008378726,0.0003969429,0.996796,0.001565961],"study_design_scores_gemma":[0.0001179213,0.00001068286,0.02016146,0.0007851926,0.00005621129,0.00002459163,0.0004297975,0.0004299799,0.00015897,0.0005956024,0.9771532,0.00007633975],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000054544,0.00006368138,0.00002789969,0.0001691717,0.00003615412,0.00001763864,0.9980458,0.00006669373,0.001518464],"genre_scores_gemma":[0.00114506,0.0005042046,0.0005191544,0.0002503539,0.00002521845,0.0001572874,0.9890021,0.0001739108,0.008222743],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.115706,"threshold_uncertainty_score":0.4738068,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02112656154285451,"score_gpt":0.2421228683370147,"score_spread":0.2209963067941602,"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."}}