{"id":"W6921698248","doi":"10.1051/0004-6361/202347601/pdf","title":"White dwarf Random Forest classification through","year":2023,"lang":"en","type":"article","venue":"Springer Link (Chiba Institute of Technology)","topic":"Stellar, planetary, and galactic studies","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Agència de Gestió d'Ajuts Universitaris i de Recerca; Generalitat de Catalunya","keywords":"Random forest; White dwarf; Stellar classification; White (mutation); Population; White noise; Pattern recognition (psychology)","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":[],"consensus_categories":[],"category_scores_codex":[0.0001364061,0.0002190106,0.0003716254,0.0002723751,0.0001878718,0.000018324,0.0003390507,0.0001545316,0.00005859366],"category_scores_gemma":[0.00004546178,0.0002015302,0.0001261593,0.0007445159,0.0003512838,0.0001765039,0.0001611791,0.000290985,0.0002905153],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001652626,"about_ca_system_score_gemma":0.00004821154,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001005595,"about_ca_topic_score_gemma":0.00002873233,"domain_scores_codex":[0.9987549,0.000009930124,0.0003724391,0.0003513555,0.0001673901,0.0003439424],"domain_scores_gemma":[0.9991275,0.00003958654,0.0001995058,0.0005188275,0.00008137754,0.00003321669],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002427937,0.00003966806,0.9373693,0.00002799257,0.0001681796,0.000003175674,0.0001261996,0.0001666362,0.0001335097,0.04665193,0.00121656,0.01407251],"study_design_scores_gemma":[0.002208925,0.00007953384,0.8121533,0.000109141,0.0001394916,0.000002915149,0.0003159457,0.0006985224,0.003287338,0.02509933,0.1554833,0.0004222473],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7788149,0.0004033358,0.006916741,0.006804231,0.002506904,0.0006894692,0.00002675008,0.0009407395,0.2028969],"genre_scores_gemma":[0.9958662,0.0001239596,0.002865368,0.00002720565,0.000387858,0.00005404647,0.00007456179,0.00002082855,0.0005799845],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2170513,"threshold_uncertainty_score":0.8218163,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0221918628140984,"score_gpt":0.2480928241846472,"score_spread":0.2259009613705488,"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."}}