{"id":"W7067733726","doi":"","title":"Modèle d'évolution sédimentaire d'un segment de rivière","year":2001,"lang":"fr","type":"other","venue":"Library and Archives Canada (Government of Canada)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Set (abstract data type); Identification (biology); Context (archaeology); Process (computing)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.00102977,0.0009385486,0.0005717191,0.002147393,0.008795306,0.007494557,0.001292694,0.00231974,0.1441609],"category_scores_gemma":[0.002915245,0.0004986725,0.0009158576,0.002796401,0.001637961,0.001775688,0.002222917,0.002465651,0.02705046],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0141796,"about_ca_system_score_gemma":0.01807351,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6015547,"about_ca_topic_score_gemma":0.7108856,"domain_scores_codex":[0.9984313,0.0001215586,0.0000359821,0.0001767418,0.0008661256,0.0003682954],"domain_scores_gemma":[0.9983534,0.0002218279,0.00007294425,0.0001893391,0.0007978469,0.0003646202],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008500585,0.0002725121,0.01063783,0.0003733169,0.00005094976,0.001045373,0.005436018,0.001268843,0.009778043,0.2007255,0.3084766,0.461085],"study_design_scores_gemma":[0.0000179307,0.00003081977,0.01292727,0.00006307958,0.000007508211,0.0002049511,0.000897388,0.0003205053,0.002463346,0.001182878,0.981865,0.00001921019],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.04023749,0.002024608,0.004991756,0.00263841,0.0006611877,0.0001920877,0.002052124,0.001030336,0.9461721],"genre_scores_gemma":[0.03565757,0.0007222527,0.002263046,0.0001757823,0.00007771772,0.00005595208,0.0009221109,0.0002584976,0.9598671],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.3984453,"threshold_uncertainty_score":0.8015836,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00301352123957063,"score_gpt":0.1406287478339148,"score_spread":0.1376152265943441,"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."}}