{"id":"W1995440297","doi":"10.1145/1414004.1414049","title":"Enhancing predictive models using principal component analysis and search based metric selection","year":2008,"lang":"en","type":"article","venue":"","topic":"Software Engineering Research","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Principal component analysis; Metric (unit); Computer science; Selection (genetic algorithm); Component (thermodynamics); Artificial intelligence; Data mining; Engineering","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":[0.006797767,0.002771593,0.002133986,0.005504386,0.0007331993,0.002245594,0.001415961,0.001076149,0.001484761],"category_scores_gemma":[0.02735979,0.0007722059,0.001531941,0.004460712,0.0006179007,0.002457478,0.001349536,0.001697713,0.0007594068],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001234985,"about_ca_system_score_gemma":0.002110049,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01455193,"about_ca_topic_score_gemma":0.009200815,"domain_scores_codex":[0.9965529,0.001870595,0.0001997091,0.000461281,0.0007516301,0.0001638744],"domain_scores_gemma":[0.9834744,0.01259563,0.0007674393,0.000759916,0.002237763,0.0001648898],"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":[0.000196163,0.0002727605,0.01073996,0.0001651225,0.0002537773,0.00009980765,0.0001643362,0.6965665,0.001766882,0.003695667,0.001987459,0.2840914],"study_design_scores_gemma":[0.000009737522,0.00003787801,0.0006100752,0.000009510319,0.00002585235,0.00001334239,0.00001248573,0.9965596,0.0003738395,0.002126664,0.0002086844,0.00001241242],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06480026,0.000483175,0.9293247,0.0004624924,0.00004747191,0.0002441831,0.0002173877,0.003033762,0.001386535],"genre_scores_gemma":[0.5589855,0.0005455402,0.4372313,0.0001330902,0.00008746709,0.0005366329,0.001075432,0.0003003069,0.001104728],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01455193,"threshold_uncertainty_score":0.03595042,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04325257420471928,"score_gpt":0.2828664932227614,"score_spread":0.2396139190180421,"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."}}