{"id":"W7045128771","doi":"","title":"Analyse des paramÃ¨tres atmosphÃ©riques\\ndes Ã©toiles naines blanches dans le voisinage solaire","year":2011,"lang":"fr","type":"other","venue":"Library and Archives Canada (Government of Canada)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Population; Distribution (mathematics); Internet of Things","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":[0.0001953803,0.0003948027,0.000294535,0.0009995092,0.0007390653,0.0007997536,0.0003970596,0.0003793437,0.00628353],"category_scores_gemma":[0.0003724614,0.0003299768,0.0005145273,0.0007508379,0.0002538496,0.0005871329,0.0003009028,0.0004710347,0.001397602],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006201666,"about_ca_system_score_gemma":0.0002815145,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009273085,"about_ca_topic_score_gemma":0.01433791,"domain_scores_codex":[0.9998693,0.000008423915,0.000002330921,0.000060263,0.00004207654,0.00001745945],"domain_scores_gemma":[0.9998361,0.00004391257,0.00002536087,0.0000223231,0.00005426943,0.00001800006],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0005154044,0.0001207441,0.1724926,0.0004043918,0.0004721867,0.0007679525,0.002468009,0.02069849,0.6870219,0.005782214,0.004483637,0.1047727],"study_design_scores_gemma":[0.00004600681,0.0001989923,0.761294,0.00008043542,0.0001876359,0.0005696194,0.001377464,0.06700482,0.1189843,0.00251549,0.04760727,0.0001339396],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9607297,0.0007891301,0.01719015,0.0001867507,0.00007506726,0.00003900653,0.001854376,0.001292919,0.01784302],"genre_scores_gemma":[0.9785653,0.0003344017,0.008431934,0.00006008789,0.00003142392,0.00004344452,0.00170783,0.0003703873,0.01045529],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009273085,"threshold_uncertainty_score":0.02102047,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004794181676109993,"score_gpt":0.1443799498656003,"score_spread":0.1395857681894904,"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."}}