{"id":"W6926529491","doi":"10.25318/2510003401-fra","title":"Gaz naturel avec les États-Unis, commerce d'exportation et d'importation mensuel, Canada","year":2019,"lang":"fr","type":"dataset","venue":"Statistics Canada Dissemination","topic":"Environmental and biological studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Limiting; Context (archaeology); Indemnity","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","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003149979,0.0006999098,0.0005649899,0.00004148592,0.0007799189,0.00007973415,0.0004583513,0.0003607482,0.003306695],"category_scores_gemma":[0.0003720412,0.0006585276,0.00005005504,0.0002529212,0.0004137439,0.0001660549,0.0002192112,0.0007339838,0.0001138195],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003507542,"about_ca_system_score_gemma":0.0004866526,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.983048,"about_ca_topic_score_gemma":0.9995006,"domain_scores_codex":[0.9957689,0.0002654192,0.0008647079,0.0008554167,0.00158436,0.0006612036],"domain_scores_gemma":[0.9975183,0.0008806871,0.0008416951,0.0004091827,0.00006687957,0.0002832676],"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":[0.00002643405,0.0001181486,0.005253417,0.0001891737,0.00007556917,0.0001148616,0.0001291478,0.0006014811,0.0004037823,0.0004529351,0.9814112,0.01122385],"study_design_scores_gemma":[0.000193643,0.0001227222,0.4484846,0.0001192528,0.0001398567,0.000008099773,0.0006890105,0.0003011274,0.0001683087,0.0001644904,0.5489186,0.00069028],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.01808617,0.0006150558,0.0005342743,0.002054872,0.001583899,0.0007312992,0.9760553,0.00001280989,0.0003262988],"genre_scores_gemma":[0.08731553,0.001617753,0.001279962,0.00140496,0.00007565868,0.00005675444,0.9046531,0.00003923959,0.003557074],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.4432312,"threshold_uncertainty_score":0.9995866,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009574308419036968,"score_gpt":0.242197373632949,"score_spread":0.232623065213912,"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."}}