{"id":"W2026390014","doi":"10.1145/2462476.2462490","title":"Evaluating student understanding of core concepts in computer architecture","year":2013,"lang":"en","type":"article","venue":"","topic":"Teaching and Learning Programming","field":"Computer Science","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Science Foundation","keywords":"Mathematics education; Subject matter; Computer science; Architecture; Curriculum; Liberal arts education; Subject (documents); Course (navigation); Core (optical fiber); Work (physics); Core curriculum; The arts; Pedagogy; Psychology; Higher education; Library science; Engineering; Visual arts","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":[0.003041889,0.0004817742,0.0003663628,0.0008780801,0.0002759534,0.001462568,0.0005592153,0.0008399388,0.003509757],"category_scores_gemma":[0.02215076,0.0001735269,0.0003005075,0.0004212646,0.0003682062,0.001290067,0.0008305392,0.001017035,0.001147867],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004289749,"about_ca_system_score_gemma":0.0004417923,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006569906,"about_ca_topic_score_gemma":0.0009825531,"domain_scores_codex":[0.9981718,0.0005340492,0.0001517742,0.0002618652,0.0006812651,0.0001991907],"domain_scores_gemma":[0.9799393,0.01148324,0.003559238,0.000624438,0.002796922,0.001596765],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007666076,0.005206483,0.8227705,0.0003223157,0.0001008804,0.0001499887,0.01455951,0.002613412,0.02277123,0.0006080847,0.001796672,0.1283344],"study_design_scores_gemma":[0.00004702472,0.004963264,0.9547446,0.00008913491,0.00004961857,0.0002671546,0.009004952,0.00968729,0.01595448,0.001093176,0.004044008,0.00005513198],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977952,0.00003224076,0.0007142435,0.00004262369,0.000002344513,0.00002743128,0.0000283666,0.00001999675,0.001337601],"genre_scores_gemma":[0.9967659,0.00008657614,0.001702537,0.00003474009,0.000004414765,0.00004098043,0.0001823161,0.000008471012,0.001174118],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003509757,"threshold_uncertainty_score":0.01608723,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1202098117365673,"score_gpt":0.3903032567225298,"score_spread":0.2700934449859625,"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."}}