{"id":"W2909081543","doi":"10.24908/pceea.v0i0.13050","title":"MAKING UNDERGRADUATE RESEARCH EXPERIENCE MORE PRODUCTIVE","year":2018,"lang":"en","type":"article","venue":"Proceedings of the Canadian Engineering Education Association (CEEA)","topic":"Engineering Education and Pedagogy","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Variety (cybernetics); Accreditation; Portfolio; Undergraduate research; Computer science; Content analysis; Medical education; Graduate students; Mathematics education; Psychology; Engineering management; Pedagogy; Engineering; Sociology; Medicine; Business; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"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":[0.02321965,0.001347311,0.00124178,0.001997637,0.005030428,0.0129989,0.002597349,0.003339806,0.03530063],"category_scores_gemma":[0.05296743,0.0007166372,0.001369413,0.001210658,0.003168386,0.009366728,0.01778994,0.005184115,0.01825102],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002882128,"about_ca_system_score_gemma":0.005143077,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002578058,"about_ca_topic_score_gemma":0.0007351993,"domain_scores_codex":[0.9701712,0.01602281,0.001528445,0.002304167,0.007443871,0.002529498],"domain_scores_gemma":[0.9104756,0.009610376,0.005587514,0.008443729,0.01898996,0.04689286],"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":[0.0003511533,0.005003107,0.01403928,0.001200369,0.00008888213,0.00267701,0.07964849,0.0005041373,0.02258907,0.01997209,0.3228466,0.5310798],"study_design_scores_gemma":[0.0001251999,0.002115991,0.00942413,0.0007962005,0.00005842159,0.003076442,0.06015179,0.0006613317,0.003738476,0.01872823,0.9010059,0.0001179102],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4064438,0.009722598,0.1114931,0.246363,0.01827455,0.003204406,0.001020018,0.01088657,0.192592],"genre_scores_gemma":[0.6414781,0.009626163,0.1172285,0.05591881,0.01231777,0.003059636,0.001935904,0.002022251,0.1564128],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03530063,"threshold_uncertainty_score":0.1227987,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03747246611013614,"score_gpt":0.3302674541955128,"score_spread":0.2927949880853766,"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."}}