{"id":"W6926414021","doi":"10.25318/3210006801-fra","title":"Revenu hors ferme total et moyen selon la source et bénéfice net d'exploitation total et moyen des exploitants agricoles","year":2019,"lang":"fr","type":"dataset","venue":"Statistics Canada Dissemination","topic":"Distributed and Parallel Computing Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"β2 adrenergic receptor; Data source","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":[0.0009258933,0.001187087,0.001153916,0.005266175,0.0009282191,0.001663709,0.001721429,0.0009320168,0.02402966],"category_scores_gemma":[0.007915285,0.0004387,0.001250773,0.01077855,0.000360705,0.00100216,0.001036711,0.001526948,0.01442828],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004715953,"about_ca_system_score_gemma":0.01008206,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.6282997,"about_ca_topic_score_gemma":0.7768103,"domain_scores_codex":[0.9989573,0.00009097291,0.0001233547,0.0002383769,0.0003514805,0.0002384598],"domain_scores_gemma":[0.9956091,0.0008376595,0.0003727672,0.0003979823,0.002477858,0.0003047205],"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":[0.0001780062,0.00002206496,0.01668358,0.0008130801,0.0001134237,0.00003284436,0.00005806223,0.0005530785,0.0001470357,0.0009060816,0.974479,0.006013727],"study_design_scores_gemma":[0.0002980924,0.00002566833,0.1124152,0.0006641439,0.0001375461,0.0001238582,0.0005721919,0.0009588976,0.0005552336,0.001600857,0.8825801,0.00006826992],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0007549562,0.000150824,0.0000509157,0.00009849429,0.00001893927,0.000007530542,0.9978818,0.0000610179,0.0009754293],"genre_scores_gemma":[0.00461036,0.0002455562,0.0003871783,0.00006521458,0.00001562007,0.00005531703,0.9918107,0.00004064819,0.002769362],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.6282997,"threshold_uncertainty_score":0.7477787,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01871253212576239,"score_gpt":0.2758721441985899,"score_spread":0.2571596120728274,"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."}}