{"id":"W4388196577","doi":"10.22318/cscl2023.104463","title":"Supporting Engineering Education Through Collaborative Design: Productive Exchange Across Interdisciplinary and Intercultural Boundaries","year":2023,"lang":"en","type":"article","venue":"Computer-supported collaborative learning/˜The œComputer-Supported Collaborative Learning Conference","topic":"Biomedical and Engineering Education","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Collaborative design; Knowledge management; Computer science; Collaborative engineering; Human–computer interaction; Engineering; Software engineering; Systems design","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","scholarly_communication","research_integrity"],"consensus_categories":["metaepi_narrow"],"category_scores_codex":[0.001749118,0.001610824,0.001451515,0.0005720461,0.002267326,0.002275427,0.001034033,0.0006822209,0.000149272],"category_scores_gemma":[0.0004995503,0.001450733,0.000179719,0.00825851,0.001189598,0.001786303,0.0009770609,0.002930148,0.0001882215],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005826756,"about_ca_system_score_gemma":0.002064783,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003421151,"about_ca_topic_score_gemma":0.00005172518,"domain_scores_codex":[0.9922379,0.001088953,0.001633179,0.001927734,0.001041858,0.002070416],"domain_scores_gemma":[0.9931739,0.001125643,0.0008616377,0.000779853,0.003471229,0.0005877301],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004348904,0.0004916131,0.001935771,0.002274354,0.00226802,0.0002941211,0.3628356,0.2817012,0.008655047,0.001243816,0.1502331,0.1876326],"study_design_scores_gemma":[0.001655982,0.002285476,0.007470725,0.001075032,0.0002050568,0.0001232928,0.03915728,0.7528216,0.002548611,0.0003899159,0.1896819,0.002585141],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3597509,0.001737156,0.6009324,0.00314151,0.02294393,0.004415347,0.000262595,0.006222024,0.0005941262],"genre_scores_gemma":[0.958891,0.0006393955,0.02933736,0.0002010984,0.006244893,0.001217999,0.001484843,0.0003568769,0.001626522],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5991401,"threshold_uncertainty_score":0.9996639,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01527420766937043,"score_gpt":0.28991762879543,"score_spread":0.2746434211260596,"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."}}