{"id":"W4387956588","doi":"10.22318/cscl2023.447639","title":"Facilitating Cross-Community Knowledge Building Through Multimodal Artifact Creation","year":2023,"lang":"en","type":"article","venue":"Computer-supported collaborative learning/The Computer-Supported Collaborative Learning Conference","topic":"Innovative Teaching and Learning Methods","field":"Psychology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Artifact (error); Situated; Multimodality; Knowledge building; Subject (documents); Computer science; Situated learning; Exploratory research; Knowledge management; Sociology; World Wide Web; Artificial intelligence; Pedagogy; Social 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","scholarly_communication","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","research_integrity","insufficient_payload"],"category_scores_codex":[0.01266557,0.002389759,0.002506013,0.001368408,0.008075617,0.002336617,0.002781098,0.001333853,0.001777811],"category_scores_gemma":[0.003534148,0.002225041,0.0005485551,0.0151485,0.002276872,0.001884199,0.001561137,0.01198811,0.002446746],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007191618,"about_ca_system_score_gemma":0.002297486,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005084194,"about_ca_topic_score_gemma":0.0001237071,"domain_scores_codex":[0.9587767,0.0301351,0.003060905,0.003163006,0.001679241,0.003185042],"domain_scores_gemma":[0.9719284,0.01344602,0.003293838,0.002196627,0.008518184,0.0006169859],"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":[0.001328043,0.00161209,0.07101157,0.0003641385,0.003151311,0.0006341908,0.3694619,0.1838325,0.008640081,0.01448547,0.03377172,0.311707],"study_design_scores_gemma":[0.006826106,0.006784095,0.2002759,0.0008054143,0.0003620232,0.0001128879,0.04198588,0.4519733,0.001141018,0.001510909,0.2840367,0.004185882],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5004167,0.0001781376,0.4786642,0.0004885676,0.008098861,0.001878765,0.0001229816,0.003360464,0.006791329],"genre_scores_gemma":[0.9240338,0.00004512315,0.05626597,0.0003734955,0.00498501,0.0006973147,0.001520827,0.0004024076,0.0116761],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4236171,"threshold_uncertainty_score":0.9999626,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05587331467548078,"score_gpt":0.4040160693321765,"score_spread":0.3481427546566957,"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."}}