{"id":"W3016050002","doi":"10.5210/fm.v28i4.13163","title":"Classifying constructive comments","year":2023,"lang":"en","type":"article","venue":"First Monday","topic":"Hate Speech and Cyberbullying Detection","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University; University of British Columbia","funders":"","keywords":"Computer science; Constructive; Annotation; Adaptation (eye); Feature (linguistics); Natural language processing; Artificial intelligence; Domain adaptation; Quality (philosophy); Linguistics; Classifier (UML); Biology; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00312419,0.001614791,0.0005041814,0.006976202,0.001538022,0.002146865,0.001216926,0.001654403,0.005566474],"category_scores_gemma":[0.03075282,0.0002902272,0.0006243397,0.0029937,0.000890426,0.002724406,0.002120456,0.001527556,0.004613807],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001281505,"about_ca_system_score_gemma":0.001423443,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00553628,"about_ca_topic_score_gemma":0.01064216,"domain_scores_codex":[0.9947061,0.001574008,0.0004598346,0.0007817978,0.00201487,0.0004634433],"domain_scores_gemma":[0.9626539,0.01842769,0.002973078,0.002232804,0.01240087,0.001311554],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001718971,0.0008222912,0.2064676,0.003388272,0.0002069675,0.003321129,0.01392012,0.01042756,0.03888717,0.01399351,0.1716179,0.5352286],"study_design_scores_gemma":[0.0001586893,0.0006755814,0.184273,0.001631299,0.0001930699,0.002991966,0.02361636,0.2003577,0.05213296,0.0151066,0.5184368,0.0004260233],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7391042,0.003606973,0.1461435,0.002772884,0.002348573,0.002323712,0.04384479,0.009741764,0.05011363],"genre_scores_gemma":[0.813736,0.001072007,0.1021327,0.000727144,0.0009327854,0.001594019,0.05303757,0.0009545147,0.02581332],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006976202,"threshold_uncertainty_score":0.01862174,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01645161755485146,"score_gpt":0.2291018135719508,"score_spread":0.2126501960170994,"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."}}