{"id":"W6996958485","doi":"","title":"Supervision et prédiction des défauts des transformateurs électriques en utilisant les techniques de machine learning","year":2024,"lang":"fr","type":"other","venue":"Depositum (Université du Québec en Abitibi-Témiscamingue)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Cégep de l'Abitibi Témiscamingue; Université du Québec en Abitibi-Témiscamingue","funders":"","keywords":"Work (physics); Filter (signal processing); Limiting; Context (archaeology)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006228966,0.0006928998,0.0005366092,0.0005296105,0.0002337749,0.0009625926,0.0004691104,0.0006498902,0.002535683],"category_scores_gemma":[0.002662823,0.0003248475,0.0005922647,0.0005209953,0.0004067968,0.0009160649,0.000312435,0.0009458506,0.0005218113],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005858894,"about_ca_system_score_gemma":0.0006967199,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0075142,"about_ca_topic_score_gemma":0.007411379,"domain_scores_codex":[0.9997577,0.00004670328,0.00001328574,0.00006190727,0.00009482608,0.00002559317],"domain_scores_gemma":[0.9988927,0.0007495095,0.00008703941,0.00007651853,0.0001732326,0.00002092383],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009714948,0.00003392213,0.004094896,0.0001047853,0.00003095705,0.00009795962,0.00008720424,0.8757429,0.0103044,0.003084566,0.0007018393,0.1056194],"study_design_scores_gemma":[0.00000306982,0.00002087411,0.001014651,0.00001020032,0.000005518466,0.00001996691,0.00002048236,0.9929485,0.003843089,0.001286976,0.0008197959,0.000006811641],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1622443,0.000684882,0.8286669,0.0004876677,0.00009486713,0.00005925576,0.0002471739,0.0009478488,0.006567081],"genre_scores_gemma":[0.9108802,0.0006177478,0.08333404,0.00007063711,0.00003370221,0.00006383735,0.0002565598,0.00007440514,0.004668999],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0075142,"threshold_uncertainty_score":0.01494092,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006221441243136312,"score_gpt":0.211714028786581,"score_spread":0.2054925875434447,"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."}}