{"id":"W6945340118","doi":"10.25318/2510006701-fra","title":"Transporteurs de pétrole par pipeline canadiens, statistiques d'exploitation mensuelles","year":2019,"lang":"fr","type":"dataset","venue":"Statistics Canada Dissemination","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Pipeline (software); Term (time); Limiting","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":[0.0003704409,0.0005959785,0.0005193516,0.00009322254,0.0003649256,0.0001242218,0.0004521012,0.0002977658,0.07062982],"category_scores_gemma":[0.0003487194,0.0007079286,0.00005802511,0.0002888857,0.0002817964,0.0001857144,0.00005617626,0.0004158549,0.0007522551],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007407404,"about_ca_system_score_gemma":0.0007126047,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7422397,"about_ca_topic_score_gemma":0.9916249,"domain_scores_codex":[0.9961988,0.0001966962,0.0008071708,0.0007288633,0.001117013,0.0009514577],"domain_scores_gemma":[0.9977413,0.000482127,0.000564042,0.0004915665,0.0001765981,0.0005442954],"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":[0.00003729785,0.0001189321,0.0009811434,0.0003245819,0.00003777993,0.0001470111,0.0003138557,0.0002108972,0.0004598847,0.001939378,0.9910835,0.00434576],"study_design_scores_gemma":[0.0003638143,0.0001200115,0.1388758,0.0001441582,0.0002814239,0.00001714327,0.003308275,0.001385576,0.0004984313,0.000214781,0.8539773,0.0008132828],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.003775226,0.0003086693,0.009017116,0.001046946,0.00119793,0.0005771085,0.9835379,0.00002305813,0.0005161171],"genre_scores_gemma":[0.01324331,0.00164323,0.001213189,0.0004456194,0.00008601587,0.00007352439,0.9785014,0.00006102863,0.004732648],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2493852,"threshold_uncertainty_score":0.9995372,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.012629407350671,"score_gpt":0.2575756045088292,"score_spread":0.2449461971581582,"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."}}