{"id":"W1767221188","doi":"","title":"Experiments with ClueWeb09: Relevance Feedback and Web Tracks","year":2009,"lang":"en","type":"article","venue":"","topic":"Web Data Mining and Analysis","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Relevance (law); Relevance feedback; Suspect; Computer science; Information retrieval; Work (physics); Data collection; World Wide Web; Statistics; Artificial intelligence; Psychology; Mathematics; 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":[0.01481194,0.002449375,0.002643629,0.002865755,0.002780359,0.002216652,0.003376988,0.003399254,0.004819493],"category_scores_gemma":[0.04788612,0.0008848242,0.001430194,0.004546863,0.001373714,0.003878242,0.002301356,0.002776332,0.003010492],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002077268,"about_ca_system_score_gemma":0.002425234,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03277485,"about_ca_topic_score_gemma":0.03746693,"domain_scores_codex":[0.9839445,0.007217213,0.00184804,0.002214095,0.003921632,0.0008545082],"domain_scores_gemma":[0.9474074,0.03476579,0.001377998,0.005765203,0.008391798,0.002291788],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.01898415,0.01983567,0.02364665,0.008689381,0.001790121,0.002522068,0.002617238,0.07088183,0.08916429,0.0017405,0.2688521,0.4912761],"study_design_scores_gemma":[0.01106554,0.02201198,0.07999143,0.0006046629,0.001333428,0.004735937,0.00333055,0.5040725,0.2098582,0.00462993,0.1568848,0.001480953],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8792982,0.01053897,0.02669333,0.001818427,0.002405945,0.004965709,0.0258855,0.03158793,0.01680596],"genre_scores_gemma":[0.7467039,0.001429063,0.1421645,0.001683581,0.0008456241,0.002814108,0.08065949,0.003058813,0.020641],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03277485,"threshold_uncertainty_score":0.07833391,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01134563912315909,"score_gpt":0.2418198543852956,"score_spread":0.2304742152621365,"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."}}