{"id":"W1999688040","doi":"10.1145/1940761.1940864","title":"Digging into Digg","year":2011,"lang":"en","type":"article","venue":"Proceedings of the 2011 iConference","topic":"Authorship Attribution and Profiling","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Digging; Computer science; Domain (mathematical analysis); Data science; Work (physics); Multimedia; World Wide Web; Human–computer interaction; Information retrieval; Engineering","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":[0.0009585689,0.0007453269,0.0004359249,0.003080444,0.002495133,0.006282941,0.0009107617,0.001622029,0.08058465],"category_scores_gemma":[0.007191595,0.0003151294,0.0003722321,0.003759296,0.002159574,0.01022016,0.004356289,0.001421212,0.02680603],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009434494,"about_ca_system_score_gemma":0.001045123,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002350503,"about_ca_topic_score_gemma":0.004894327,"domain_scores_codex":[0.9992792,0.0002161652,0.00003903534,0.0001654834,0.0001844403,0.0001157308],"domain_scores_gemma":[0.9975542,0.0007456497,0.0001183685,0.0007777198,0.000466641,0.0003374318],"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":[0.0002488111,0.00006037209,0.004510756,0.0003656046,0.00002281945,0.0009893217,0.00973577,0.0008669163,0.002526066,0.3449721,0.1927721,0.4429294],"study_design_scores_gemma":[0.0000114176,0.0000480144,0.001288008,0.0002898485,0.00001336861,0.0006519585,0.004963904,0.001463466,0.0009186565,0.09493324,0.8953906,0.00002755852],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.03973855,0.003523134,0.09839708,0.01030116,0.002536034,0.0002040696,0.003037586,0.005205403,0.8370569],"genre_scores_gemma":[0.354295,0.004809033,0.08258328,0.005185982,0.0006973406,0.0002001073,0.007030652,0.003245923,0.5419527],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.08058465,"threshold_uncertainty_score":0.2695825,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05148322709674232,"score_gpt":0.2334094173967552,"score_spread":0.1819261903000129,"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."}}