{"id":"W6888867940","doi":"10.25318/2110013701-fra","title":"Recettes pour les entreprises à la distribution cinématographique, vidéo et audiovisuelle et la distribution en gros des vidéocassettes, selon les premiers marchés visés, inactif","year":2020,"lang":"fr","type":"dataset","venue":"Statistics Canada Dissemination","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Distribution (mathematics); Triangular distribution; Noncentral chi-squared distribution","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":[0.0008875034,0.001597925,0.000975361,0.008190807,0.001101706,0.002539815,0.001568789,0.001115085,0.04474556],"category_scores_gemma":[0.00902654,0.000665703,0.00100263,0.01566072,0.0005609684,0.001531396,0.001171329,0.00138551,0.03589567],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007755397,"about_ca_system_score_gemma":0.01263591,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6905367,"about_ca_topic_score_gemma":0.7830428,"domain_scores_codex":[0.9982041,0.0001533435,0.0001968751,0.0003992317,0.0007444005,0.0003020663],"domain_scores_gemma":[0.993143,0.001199939,0.0005387071,0.0006348077,0.004136465,0.0003471338],"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":[0.00006996293,0.00001670866,0.003791615,0.0008462727,0.00003048716,0.00002516704,0.00006272046,0.0003197071,0.0001458745,0.0006491909,0.9870046,0.007037663],"study_design_scores_gemma":[0.00005514772,0.000008789176,0.02632465,0.0004158989,0.00003236596,0.00005141701,0.0002840818,0.000402372,0.0005127371,0.0004056181,0.9714693,0.00003758636],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003354759,0.0001525487,0.00007539571,0.00006226659,0.00002022222,0.00001253459,0.9971864,0.000166732,0.001988509],"genre_scores_gemma":[0.00156931,0.0002544601,0.0004341794,0.00004086946,0.0000118391,0.00006344842,0.9942659,0.00006982828,0.003290275],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3094633,"threshold_uncertainty_score":0.6225715,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01024582192111431,"score_gpt":0.2860253915496007,"score_spread":0.2757795696284864,"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."}}