{"id":"W342589544","doi":"","title":"York University at TREC 2012: CrowdSourcing Track.","year":2012,"lang":"en","type":"article","venue":"Text REtrieval Conference","topic":"Information Retrieval and Search Behavior","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Crowdsourcing; Computer science; Quality (philosophy); Work (physics); Crowdsourcing software development; Data science; Control (management); Information retrieval; World Wide Web; Artificial intelligence; 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":[0.01987685,0.007234418,0.00445744,0.009414261,0.009248908,0.009217993,0.005930183,0.004843805,0.08711207],"category_scores_gemma":[0.02264315,0.001461212,0.001348932,0.008401699,0.002214527,0.008890569,0.004935153,0.006895278,0.08572266],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0125611,"about_ca_system_score_gemma":0.01893056,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3457804,"about_ca_topic_score_gemma":0.4783251,"domain_scores_codex":[0.9878335,0.003597973,0.0006569964,0.001323473,0.005505962,0.00108215],"domain_scores_gemma":[0.9703686,0.00359933,0.001033894,0.004514141,0.01497625,0.005507737],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004827742,0.00006008073,0.00009386343,0.0001389481,0.00001029155,0.00001022141,0.00002034499,0.0003505086,0.0002113424,0.0002812657,0.9910572,0.007717749],"study_design_scores_gemma":[0.0003784115,0.0001516333,0.004926038,0.0004251365,0.00004860865,0.00006172384,0.0003434896,0.009215571,0.002834974,0.005097433,0.9762915,0.0002255778],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.008757146,0.01700005,0.02163902,0.03626464,0.01773245,0.005122889,0.6697195,0.03786725,0.185897],"genre_scores_gemma":[0.02087327,0.004106049,0.02560998,0.003293392,0.002023505,0.003410425,0.7230422,0.003683373,0.2139579],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.3457804,"threshold_uncertainty_score":0.6875354,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04766109456374461,"score_gpt":0.2510287572091137,"score_spread":0.2033676626453691,"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."}}