{"id":"W2406847633","doi":"","title":"Overview of the TREC 2012 Crowdsourcing Track.","year":2012,"lang":"en","type":"article","venue":"","topic":"Information Retrieval and Search Behavior","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Crowdsourcing; Track (disk drive); Computer science; Relevance (law); World Wide Web; Task (project management); Set (abstract data type); Information retrieval; Data science; 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":[0.008366762,0.002110522,0.001537392,0.01066455,0.004407905,0.005228162,0.002068205,0.002381629,0.03841864],"category_scores_gemma":[0.008963435,0.0007432413,0.001145973,0.0100343,0.0004634238,0.003567025,0.00294933,0.002674337,0.0382989],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005784663,"about_ca_system_score_gemma":0.01084068,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1357614,"about_ca_topic_score_gemma":0.2305448,"domain_scores_codex":[0.9927667,0.0009782918,0.000357449,0.001121548,0.003939748,0.0008361842],"domain_scores_gemma":[0.9851955,0.001120092,0.0005250928,0.001325788,0.009953835,0.001879593],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001367556,0.0001286664,0.0005686755,0.000387311,0.00003553981,0.00002204769,0.00004927405,0.0003683882,0.001516947,0.0005881159,0.9477213,0.04847698],"study_design_scores_gemma":[0.000135297,0.0002214762,0.01010942,0.0002850408,0.00008120138,0.00008286993,0.0001732908,0.002828073,0.003702806,0.001827437,0.9804319,0.0001211072],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.01398914,0.02488877,0.03959494,0.01606422,0.0142201,0.009187333,0.6344172,0.02622332,0.2214151],"genre_scores_gemma":[0.02770063,0.006143215,0.0385436,0.00316601,0.002561486,0.004306968,0.7574293,0.002335304,0.1578136],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1357614,"threshold_uncertainty_score":0.2699425,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07026204103805114,"score_gpt":0.3066848247179745,"score_spread":0.2364227836799233,"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."}}