{"id":"W4248677059","doi":"10.2316/journal.213.2015.4.213-1071","title":"TEST CLUSTER SELECTION USING COVER COEFFICIENTS","year":2015,"lang":"en","type":"article","venue":"Software Engineering","topic":"Educational Technology and Assessment","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Selection (genetic algorithm); Cover (algebra); Statistics; Test (biology); Cluster (spacecraft); Mathematics; Computer science; Artificial intelligence; Biology; Engineering; Ecology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.002544473,0.001179972,0.001630104,0.00988021,0.001107373,0.002022335,0.001359169,0.001416976,0.002231214],"category_scores_gemma":[0.02778849,0.0005063438,0.001244244,0.004230089,0.0007791675,0.00169181,0.001874302,0.0009248508,0.0009122303],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00144672,"about_ca_system_score_gemma":0.001588777,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006785322,"about_ca_topic_score_gemma":0.005997154,"domain_scores_codex":[0.9961332,0.0006807853,0.0001869776,0.0006031633,0.001906079,0.0004897806],"domain_scores_gemma":[0.9871635,0.007199802,0.00110564,0.001125121,0.002943503,0.0004623998],"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":[0.0007966371,0.0002789647,0.03212301,0.0003184206,0.0002909662,0.0005265442,0.00054604,0.3181184,0.0301135,0.01069694,0.007667493,0.598523],"study_design_scores_gemma":[0.00002919719,0.000116511,0.006047172,0.0000285339,0.00005410994,0.000232113,0.0001147161,0.9785944,0.00803998,0.005277894,0.001435922,0.00002949505],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2494613,0.0006380846,0.7408053,0.0003127363,0.00004423537,0.000404509,0.0006499646,0.002601046,0.005082761],"genre_scores_gemma":[0.8315279,0.0002043192,0.1643554,0.00007813983,0.0000578121,0.000274375,0.001667763,0.0004527823,0.001381524],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00988021,"threshold_uncertainty_score":0.01349169,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01985422108958538,"score_gpt":0.2629163778824063,"score_spread":0.2430621567928209,"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."}}