{"id":"W2921458742","doi":"10.1145/3308558.3316756","title":"Thanks for Stopping By: A Study of “Thanks” Usage on Wikimedia","year":2019,"lang":"en","type":"article","venue":"","topic":"Wikis in Education and Collaboration","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; World Wide Web","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":[],"consensus_categories":[],"category_scores_codex":[0.0004552664,0.00004686491,0.00008704586,0.00004408916,0.0001164398,0.00003378735,0.0001253919,0.00004296891,0.0005285704],"category_scores_gemma":[0.0001350678,0.00004226207,0.000019996,0.0002375133,0.00002700688,0.0001178695,0.000008401101,0.00003528165,0.00004482141],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004576471,"about_ca_system_score_gemma":0.0001459124,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000516406,"about_ca_topic_score_gemma":0.001367027,"domain_scores_codex":[0.9992934,0.00007735551,0.0001225215,0.0001323216,0.000257706,0.0001167347],"domain_scores_gemma":[0.9994791,0.000164988,0.00006889727,0.0001256093,0.0001225458,0.00003890312],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0002083218,0.005034029,0.06799477,0.00005456954,0.000109388,2.824462e-7,0.4606968,0.00006308305,0.01002479,0.2506103,0.1610752,0.04412846],"study_design_scores_gemma":[0.002174442,0.001760651,0.01253932,0.00003352611,0.00003106368,4.942604e-8,0.6200736,0.0001860009,0.003161406,0.001897046,0.3577873,0.0003556104],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.894459,0.00001059613,0.0001065099,0.0009213162,0.0007437926,0.0008774574,0.000004019481,0.00002790098,0.1028494],"genre_scores_gemma":[0.978999,0.00000387918,0.0001240266,0.0002734418,0.0001177717,0.00004986129,0.000003730835,0.00000458826,0.02042371],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2487133,"threshold_uncertainty_score":0.5787476,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02471651896191927,"score_gpt":0.3667327423497502,"score_spread":0.3420162233878309,"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."}}