{"id":"W3126814195","doi":"10.51357/jei.v2i1.105","title":"Developing Coding Structures For Becoming Affect-Savy in the Fully Online Community Model","year":2021,"lang":"en","type":"article","venue":"Journal of Educational Informatics","topic":"Impact of Technology on Adolescents","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Surprise; Sadness; Psychology; Facial expression; Body language; Affect (linguistics); Social psychology; Coding (social sciences); Facilitation; Cognitive psychology; Communication; Anger","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":[0.01211238,0.0005995844,0.0002252468,0.002581765,0.001611529,0.003225256,0.001085246,0.0008970324,0.00375652],"category_scores_gemma":[0.04126174,0.000438117,0.0006993468,0.0009054068,0.004818521,0.004134783,0.003621567,0.001492267,0.0006474667],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002267049,"about_ca_system_score_gemma":0.002224036,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004270126,"about_ca_topic_score_gemma":0.004789891,"domain_scores_codex":[0.9925821,0.005012765,0.0004659728,0.0005867954,0.00101966,0.0003328066],"domain_scores_gemma":[0.9728344,0.01606324,0.002462349,0.003320018,0.00469353,0.0006264964],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.0003291092,0.0003446469,0.06210319,0.0005220841,0.00006198782,0.0005723909,0.2242094,0.004671747,0.01000733,0.4938841,0.00273425,0.2005598],"study_design_scores_gemma":[0.0001385413,0.0007627,0.07970899,0.001297819,0.0001523583,0.001506194,0.1517562,0.1966788,0.009652955,0.4950321,0.06297359,0.0003399542],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3014444,0.0001053242,0.6502286,0.001352892,0.0001410508,0.002283505,0.0004158973,0.0004141443,0.0436142],"genre_scores_gemma":[0.7382143,0.0000554047,0.2567364,0.0001287998,0.0000202299,0.002634075,0.0003203045,0.00006570235,0.001824796],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01211238,"threshold_uncertainty_score":0.06405717,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1181711619868752,"score_gpt":0.4292303743788032,"score_spread":0.311059212391928,"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."}}