{"id":"W2115089173","doi":"10.1109/cseet.2005.30","title":"Software Engineering Education From Indian Perspective","year":2005,"lang":"en","type":"article","venue":"","topic":"Teaching and Learning Programming","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Social software engineering; Artifact (error); Software development; Personal software process; Software Engineering Process Group; Software peer review; Software deployment; Software; Software engineering; Software construction; Engineering management; Perspective (graphical); Software analytics; Engineering; Computer science; Artificial intelligence; Operating system","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007523976,0.00005719105,0.0000445,0.00006181868,0.00006312684,0.0001294519,0.0002574977,0.00002697957,0.00002224403],"category_scores_gemma":[0.0001186252,0.00005513946,0.00002343779,0.0001095566,0.000004140461,0.0002774356,0.00004737478,0.0001481886,0.0001123103],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008283513,"about_ca_system_score_gemma":0.00006186283,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006222276,"about_ca_topic_score_gemma":0.0000224207,"domain_scores_codex":[0.999544,0.00001527107,0.00005625312,0.0001841066,0.00008076143,0.0001195683],"domain_scores_gemma":[0.9996614,0.00004802059,0.0000189113,0.0001915557,0.00002754467,0.00005258862],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[2.708912e-7,0.00003809284,0.001553207,0.000001484653,0.000006555857,6.98812e-7,0.01151477,0.0005596282,0.00002286803,0.02419488,0.0003135996,0.961794],"study_design_scores_gemma":[0.0004319392,0.00009818771,0.0937402,0.0001184903,0.00001157323,0.00003070406,0.004276553,0.03869385,0.001039368,0.001224296,0.8594308,0.0009039767],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05216222,0.0002424502,0.9440575,0.001796442,0.0002742856,0.00004426101,2.070262e-7,0.000817486,0.0006051353],"genre_scores_gemma":[0.5293756,4.498384e-7,0.4700306,0.0001299695,0.0001418105,0.000003293337,9.573911e-7,0.000003285107,0.000313987],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9608899,"threshold_uncertainty_score":0.2248522,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00583388960939344,"score_gpt":0.2344718014606515,"score_spread":0.2286379118512581,"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."}}