{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.005683481,0.0003120989,0.0006073186,0.001641935,0.00222204,0.003582819,0.0008305962,0.001175105,0.003149018],"category_scores_gemma":[0.04192102,0.0004966915,0.0003135034,0.001476358,0.001545734,0.003714615,0.002775938,0.001906845,0.0009193565],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008281123,"about_ca_system_score_gemma":0.0008454815,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003723201,"about_ca_topic_score_gemma":0.008221159,"domain_scores_codex":[0.9952413,0.002915336,0.0002726624,0.0005069871,0.0006548551,0.0004088276],"domain_scores_gemma":[0.9430099,0.03656992,0.01092044,0.001832813,0.003039772,0.004627215],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0006318754,0.002697729,0.4551578,0.0004377537,0.0001594381,0.0005482073,0.5101032,0.00008867159,0.002297559,0.0007481715,0.002575045,0.02455461],"study_design_scores_gemma":[0.00005194226,0.0006690391,0.8035852,0.0001237554,0.00005499376,0.0002471209,0.1855379,0.0004340011,0.0006598153,0.0004315063,0.008115661,0.00008901986],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9982111,0.00008065016,0.0001300151,0.00009653563,0.000009759893,0.00002927162,0.00007719949,0.000006975461,0.001358508],"genre_scores_gemma":[0.9978727,0.0001009925,0.0002941499,0.000149439,0.00001947341,0.0001239464,0.0001325105,0.00002057106,0.001286166],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9983581,"threshold_uncertainty_score":0.03005749,"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."}}