{"id":"W89847086","doi":"","title":"A Mile Wide But Not An Inch Deep: Striving to Promote Deep Understanding and Learning in University Science Laboratories","year":2014,"lang":"en","type":"article","venue":"Scholarship@Western (Western University)","topic":"Science Education and Pedagogy","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Session (web analytics); Comprehension; Deep learning; Curriculum; Computer science; Mathematics education; Psychology; Artificial intelligence; Pedagogy; World Wide Web","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":[0.00722779,0.0007346048,0.0003972737,0.0007408719,0.004564239,0.00601017,0.002618119,0.002686449,0.003183753],"category_scores_gemma":[0.009584349,0.0005516336,0.000534843,0.0004591829,0.002889832,0.005108334,0.008620122,0.003855521,0.001483145],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009726602,"about_ca_system_score_gemma":0.004583235,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005926927,"about_ca_topic_score_gemma":0.002058438,"domain_scores_codex":[0.9971636,0.001394615,0.00009639902,0.0003626227,0.0004832355,0.0004995852],"domain_scores_gemma":[0.9940575,0.00167226,0.0005188444,0.000574203,0.0004487243,0.002728493],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.0003126038,0.01273218,0.01419082,0.001245743,0.00004903951,0.001464616,0.09840471,0.001603757,0.04792007,0.01317906,0.04908099,0.7598165],"study_design_scores_gemma":[0.000749252,0.01020532,0.09690581,0.00253059,0.0002658207,0.0063442,0.2927512,0.01034121,0.09584653,0.08422804,0.3991344,0.000697548],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8304067,0.001161655,0.07200888,0.03477095,0.001010415,0.001133383,0.00004090381,0.001918405,0.05754872],"genre_scores_gemma":[0.8249037,0.001266097,0.1517228,0.004430525,0.0002006467,0.0008670274,0.00007533185,0.000173858,0.01635998],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00722779,"threshold_uncertainty_score":0.0382247,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.148011375443494,"score_gpt":0.3710394772806522,"score_spread":0.2230281018371581,"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."}}