{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001820637,0.0009649466,0.0008978554,0.0002845253,0.0005079202,0.00136509,0.001198988,0.0005046883,0.00004764124],"category_scores_gemma":[0.001518679,0.001099991,0.0001174957,0.0009284324,0.0001680311,0.0009830353,0.0004674981,0.0009997601,0.00009213578],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009799763,"about_ca_system_score_gemma":0.002089966,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.07038847,"about_ca_topic_score_gemma":0.1615141,"domain_scores_codex":[0.9926949,0.001817787,0.001257865,0.001332061,0.001886635,0.001010754],"domain_scores_gemma":[0.9931123,0.003262528,0.001246823,0.00100734,0.0009275988,0.0004434354],"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":[0.00002876922,0.0002057502,0.0000629493,0.0009190082,0.0001381624,0.0002843683,0.00429971,0.03168378,0.0001011476,0.01215008,0.9436502,0.006476062],"study_design_scores_gemma":[0.002788425,0.001653745,0.134268,0.01033943,0.0008797435,0.002005271,0.009765517,0.1917671,0.0001477142,0.005518739,0.6334625,0.00740381],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.01101555,0.000243711,0.3074172,0.0005798702,0.002428902,0.0007928609,0.6771652,0.00008908848,0.000267692],"genre_scores_gemma":[0.1618594,0.000199113,0.00875221,0.0003064837,0.0002180642,0.00008929864,0.8232649,0.0000989624,0.005211631],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3101878,"threshold_uncertainty_score":0.9996716,"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."}}