{"id":"W6931523361","doi":"10.5281/zenodo.5451815","title":"Temelucha interruptor","year":2016,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Statistical Methods and Applications","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Product (mathematics); Field (mathematics); Identification (biology); Filter (signal processing)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001793646,0.0005771657,0.0004756604,0.001836458,0.002501709,0.0006567736,0.0006897121,0.0007759469,0.01963223],"category_scores_gemma":[0.0005029042,0.0002478921,0.0002208916,0.001160515,0.001137312,0.001019952,0.001472413,0.0007730065,0.004497404],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007925293,"about_ca_system_score_gemma":0.0004703081,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008663609,"about_ca_topic_score_gemma":0.0126983,"domain_scores_codex":[0.9997669,0.00002597599,0.00001922707,0.0001055986,0.00004596758,0.00003629897],"domain_scores_gemma":[0.9998778,0.000020933,0.00004233797,0.00001535736,0.00002571805,0.00001782226],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001216774,0.0001372177,0.03945547,0.001475232,0.000139391,0.00286523,0.005646974,0.001137053,0.03499019,0.03637261,0.03482468,0.8417391],"study_design_scores_gemma":[0.0001328352,0.0003222932,0.2233028,0.0005011934,0.0001856523,0.005300449,0.002163979,0.0005023327,0.003186136,0.004136336,0.7602086,0.00005732704],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.5140744,0.01922102,0.01009218,0.001168011,0.001378616,0.0005961276,0.007650713,0.001436919,0.4443821],"genre_scores_gemma":[0.930348,0.002845982,0.006218512,0.0007225314,0.0003551051,0.0001989398,0.00427039,0.0001618869,0.0548787],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.01963223,"threshold_uncertainty_score":0.06567633,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1433455391336968,"score_gpt":0.362165204640606,"score_spread":0.2188196655069092,"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."}}