{"id":"W2134280934","doi":"10.1109/step.2003.6","title":"Bloom’s Taxonomy Levels for Three Software Engineer Profiles","year":2005,"lang":"en","type":"article","venue":"","topic":"Software Engineering Techniques and Practices","field":"Computer Science","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"Háskóli Íslands","keywords":"Software engineering; Social software engineering; Computer science; Software Engineering Process Group; Personal software process; Software development; Taxonomy (biology); Software construction; Software peer review; Software requirements; Software quality; Software; Engineering management; Engineering; Programming language; Ecology","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":[0.009301397,0.0009155557,0.0007337061,0.00896824,0.007187783,0.006997521,0.001785247,0.003632854,0.005597309],"category_scores_gemma":[0.02318336,0.0008147198,0.001282647,0.007338365,0.005886256,0.01242599,0.005946558,0.003960054,0.002696502],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01323776,"about_ca_system_score_gemma":0.01543737,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01432228,"about_ca_topic_score_gemma":0.01804752,"domain_scores_codex":[0.9900149,0.003742089,0.001807463,0.0008279933,0.002819947,0.0007876186],"domain_scores_gemma":[0.9846527,0.005365718,0.001180158,0.0009469221,0.006221513,0.001632973],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006042611,0.0001106223,0.006154345,0.0003945867,0.000009042553,0.0001614295,0.01032519,0.0009097159,0.000625592,0.8514748,0.03468964,0.0950847],"study_design_scores_gemma":[0.00005432002,0.0001936891,0.005086923,0.0009941482,0.00001764977,0.0005554573,0.01128602,0.005713268,0.0008365773,0.5883302,0.3868338,0.00009791695],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04028647,0.005294199,0.6002018,0.04574236,0.0009845232,0.003699609,0.002053361,0.001002255,0.3007355],"genre_scores_gemma":[0.1506112,0.004060017,0.808988,0.003268036,0.0001303999,0.00332529,0.001522393,0.0001195059,0.0279751],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01432228,"threshold_uncertainty_score":0.0960471,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07118166538348805,"score_gpt":0.2781320332400004,"score_spread":0.2069503678565124,"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."}}