{"id":"W2043893472","doi":"10.1145/2132176.2132232","title":"VDMs for finding and re-finding web search results","year":2012,"lang":"en","type":"article","venue":"Proceedings of the 2012 iConference","topic":"Web Data Mining and Analysis","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Computer science; World Wide Web; Information retrieval","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":[0.00139152,0.0001324654,0.0001974504,0.0001273512,0.0002414581,0.0002002585,0.001161939,0.00006421653,0.00000476787],"category_scores_gemma":[0.0004227007,0.00009446192,0.00007369435,0.0003726753,0.00008928677,0.001342119,0.0006611489,0.0001479831,0.000006816873],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001981522,"about_ca_system_score_gemma":0.00004592547,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002280975,"about_ca_topic_score_gemma":0.000002530135,"domain_scores_codex":[0.9987111,0.000009459936,0.0002605222,0.0003071727,0.0002689026,0.0004428068],"domain_scores_gemma":[0.9990794,0.0001682697,0.0002060621,0.0002373639,0.0001894483,0.0001194515],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001289507,0.000276333,0.1917466,0.0007036328,0.0002349911,3.264751e-7,0.02006936,0.000008654523,0.2059086,0.4619478,0.02767484,0.09129989],"study_design_scores_gemma":[0.00655629,0.0008122448,0.1600009,0.002782426,0.0005844802,0.0001205337,0.008061176,0.2263768,0.5109869,0.01734611,0.06311775,0.003254461],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.97707,0.0004531996,0.008075198,0.003445076,0.0004109939,0.0003602052,0.00006179763,0.0001145985,0.01000898],"genre_scores_gemma":[0.9832287,0.00003481464,0.01560234,0.00004484493,0.0001164557,0.00001246175,0.000001555282,0.000007818509,0.0009510087],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4446017,"threshold_uncertainty_score":0.3852045,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.078359101481355,"score_gpt":0.2996684287116851,"score_spread":0.2213093272303301,"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."}}