{"id":"W2160885572","doi":"10.18438/b85p4q","title":"What Can Students’ Bibliographies Tell Us?- Evidence Based Information Skills Teaching for Engineering Students","year":2006,"lang":"en","type":"article","venue":"Evidence Based Library and Information Practice","topic":"Health Sciences Research and Education","field":"Health Professions","cited_by":52,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Citation; Computer science; The Internet; Mathematics education; Strengths and weaknesses; Quality (philosophy); Variety (cybernetics); Psychology; World Wide Web; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts","scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.005268424,0.0002303549,0.000220318,0.003289449,0.001452458,0.001883919,0.0006301794,0.0001745734,0.0001398807],"category_scores_gemma":[0.00780083,0.000206895,0.00006450607,0.003025482,0.00006842186,0.4009329,0.0001689854,0.000722994,0.000102332],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006624449,"about_ca_system_score_gemma":0.0009145864,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002322426,"about_ca_topic_score_gemma":0.000001668307,"domain_scores_codex":[0.9959629,0.0006886811,0.001185173,0.0002209454,0.001237256,0.0007050944],"domain_scores_gemma":[0.9878162,0.01037087,0.0007780653,0.00034982,0.0003362574,0.0003487974],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00144179,0.0005013926,0.7272094,0.006812535,0.00004860396,0.00000232494,0.006127391,0.006075414,0.0001035651,0.01067789,0.226863,0.01413671],"study_design_scores_gemma":[0.0009175806,0.0003323003,0.388358,0.004479604,0.00003056428,0.000002013167,0.005812016,0.01374409,0.0001903766,0.00004279925,0.5857775,0.0003132212],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7938835,0.002454152,0.04508809,0.1435029,0.004574297,0.008443479,0.0001043048,0.000739588,0.001209666],"genre_scores_gemma":[0.7802542,0.02394235,0.02461087,0.1670307,0.0009742373,0.001893718,0.0006677497,0.00003895604,0.0005872151],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.399049,"threshold_uncertainty_score":0.9998475,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03915260585087815,"score_gpt":0.4182561249079297,"score_spread":0.3791035190570516,"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."}}