{"id":"W1548053363","doi":"10.1007/3-540-46502-2_9","title":"Parallel Predictor Generation","year":2002,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Machine Learning and Data Classification","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"","keywords":"Computer science; Training set; Range (aeronautics); Regression; Set (abstract data type); Data mining; Machine learning; Artificial intelligence; Data set; Statistics; Mathematics","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":[0.0006231643,0.00125752,0.00110218,0.00103921,0.0008642804,0.001318202,0.001567705,0.0008489726,0.06283176],"category_scores_gemma":[0.002104989,0.0007392538,0.0009337402,0.001119333,0.0003387764,0.001370744,0.001588888,0.001443044,0.01873347],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004865366,"about_ca_system_score_gemma":0.001652637,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002265931,"about_ca_topic_score_gemma":0.00442174,"domain_scores_codex":[0.9995353,0.00006435267,0.00002781115,0.0001630263,0.0001355269,0.00007406749],"domain_scores_gemma":[0.9992223,0.0001565474,0.00002589125,0.0003321551,0.0002186155,0.00004455665],"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":[0.0006894986,0.0002272671,0.001423383,0.0001696701,0.0001017624,0.0002447226,0.00005969748,0.04497331,0.01556738,0.0224997,0.08376084,0.8302828],"study_design_scores_gemma":[0.0002025422,0.0001644782,0.0008638311,0.00004608041,0.0001054526,0.0003627915,0.00004728037,0.8452789,0.04464994,0.05393643,0.05428716,0.00005509478],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01378755,0.0004052356,0.9352037,0.000377947,0.0007854311,0.0002906007,0.001927656,0.02707857,0.02014319],"genre_scores_gemma":[0.2186384,0.0003862008,0.6964603,0.0005167433,0.0004364325,0.0006680144,0.008436099,0.003264614,0.07119318],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.06283176,"threshold_uncertainty_score":0.2101932,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02959770801902471,"score_gpt":0.2495188121659152,"score_spread":0.2199211041468905,"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."}}