{"id":"W2901982539","doi":"","title":"Scripting and Orchestrating Learning Communities: A Role for Learning Analytics.","year":2017,"lang":"en","type":"article","venue":"Computer Supported Collaborative Learning","topic":"Online Learning and Analytics","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Scripting language; Learning analytics; Analytics; Data science; Human–computer interaction; World Wide Web; Software engineering; Programming language","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"],"consensus_categories":[],"category_scores_codex":[0.001631328,0.0005140945,0.0007030561,0.0003311324,0.00570652,0.003657581,0.001522315,0.0002118727,0.00001548872],"category_scores_gemma":[0.001127458,0.0005480554,0.000152442,0.000515087,0.0002940523,0.001467765,0.001162628,0.001956748,0.00001511998],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007839495,"about_ca_system_score_gemma":0.0003391526,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001078772,"about_ca_topic_score_gemma":0.00004631444,"domain_scores_codex":[0.9965517,0.0006888832,0.0006580427,0.0007964463,0.0004154225,0.0008895307],"domain_scores_gemma":[0.9959193,0.0009057093,0.00114442,0.0008131096,0.0009326511,0.000284803],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007152258,0.0001807902,0.370775,0.0002954081,0.0006427275,0.0001305436,0.04258084,0.2138064,0.001800442,0.02245256,0.000465612,0.3467982],"study_design_scores_gemma":[0.001095765,0.0008227507,0.005589353,0.0002745461,0.00005288952,0.00002891933,0.006891311,0.9624468,0.0001550043,0.0007465855,0.0212511,0.0006449814],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1714012,0.0003738654,0.8209415,0.002453289,0.0003981325,0.000493255,0.000004733014,0.0009287516,0.003005243],"genre_scores_gemma":[0.8646391,0.00007236893,0.1324354,0.0001321098,0.0004270931,0.00003295,0.00005249308,0.00006196331,0.002146538],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7486404,"threshold_uncertainty_score":0.9996971,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02359888831048644,"score_gpt":0.2933381023513165,"score_spread":0.26973921404083,"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."}}