{"id":"W2151877107","doi":"10.1109/tse.2004.69","title":"A cognitive-based mechanism for constructing software inspection teams","year":2004,"lang":"en","type":"article","venue":"IEEE Transactions on Software Engineering","topic":"Software Engineering Research","field":"Computer Science","cited_by":52,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Software inspection; Mechanism (biology); Process (computing); Selection (genetic algorithm); Software; Cognition; Artificial intelligence; Software engineering; Software development; Software quality","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":[0.008816103,0.0009072998,0.0004892036,0.003747341,0.003014708,0.004589808,0.004354219,0.002488966,0.007086209],"category_scores_gemma":[0.02933982,0.0007098771,0.0013853,0.001562401,0.003753279,0.004776124,0.00468692,0.001577381,0.001468954],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002190372,"about_ca_system_score_gemma":0.003458404,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00231458,"about_ca_topic_score_gemma":0.002135221,"domain_scores_codex":[0.9935916,0.002191575,0.0004100662,0.001322259,0.001941071,0.0005434114],"domain_scores_gemma":[0.9864545,0.004596057,0.002367455,0.002700994,0.002422956,0.001458096],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000269746,0.0007054185,0.009203213,0.0002458336,0.0002365356,0.0005533362,0.006779901,0.03747665,0.01688124,0.7016523,0.005129452,0.2208664],"study_design_scores_gemma":[0.0003881864,0.0009899476,0.005837909,0.0001877068,0.0002458149,0.0009288968,0.002091234,0.347094,0.0138326,0.5870764,0.04101175,0.0003154235],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03937142,0.00009165079,0.9387974,0.0008729801,0.00008930394,0.0004215842,0.00003781901,0.001135196,0.01918266],"genre_scores_gemma":[0.4890806,0.00007565448,0.5029449,0.0002307975,0.00007980851,0.0008269931,0.00009308821,0.00007363953,0.006594443],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008816103,"threshold_uncertainty_score":0.0466246,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01559601964481879,"score_gpt":0.2488472150203617,"score_spread":0.2332511953755429,"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."}}