{"id":"W2981460216","doi":"10.1007/s40979-019-0045-1","title":"Developing a university-wide academic integrity E-learning tutorial: a Canadian case","year":2019,"lang":"en","type":"article","venue":"International Journal for Educational Integrity","topic":"Academic integrity and plagiarism","field":"Social Sciences","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"MacEwan University","funders":"","keywords":"Academic integrity; Misconduct; Experiential learning; Mathematics education; Higher education; Learning development; Personal Integrity; Scientific integrity; Computer science; Psychology; Pedagogy; Engineering ethics; Political science; Engineering; Library science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.007842083,0.0004478137,0.000308229,0.001309294,0.02219944,0.00500901,0.003441404,0.004280373,0.004149712],"category_scores_gemma":[0.01753699,0.0003420229,0.0004301505,0.001877431,0.004356515,0.002385701,0.005717468,0.004213221,0.0005964584],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03816849,"about_ca_system_score_gemma":0.07356948,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6469489,"about_ca_topic_score_gemma":0.8532164,"domain_scores_codex":[0.9923502,0.003031725,0.0002101889,0.0003774877,0.001929578,0.002100886],"domain_scores_gemma":[0.984799,0.002669217,0.000540952,0.0004498033,0.003662855,0.00787815],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0002705681,0.004635334,0.0520625,0.0007757348,0.00004509921,0.09671798,0.3948109,0.00718362,0.007177036,0.09297854,0.0818387,0.261504],"study_design_scores_gemma":[0.00008779335,0.0008907632,0.02191105,0.0007580754,0.00005371339,0.0185311,0.4300168,0.01189268,0.007943418,0.006443247,0.5011952,0.0002761607],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8470608,0.0009562707,0.01261758,0.03878189,0.0004011431,0.0009644963,0.0002111097,0.0002549536,0.09875175],"genre_scores_gemma":[0.9513005,0.001178355,0.01473183,0.002582762,0.00004777102,0.0001682318,0.00009935486,0.0001110915,0.02978005],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9957196,"threshold_uncertainty_score":0.7102605,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0487292806891621,"score_gpt":0.3804978260216336,"score_spread":0.3317685453324715,"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."}}