{"id":"W218939381","doi":"","title":"York University at TREC 2012: Microblog Track.","year":2012,"lang":"en","type":"article","venue":"Text REtrieval Conference","topic":"Advanced Image and Video Retrieval Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Microblogging; Social media; Computer science; Track (disk drive); Task (project management); Information retrieval; Component (thermodynamics); World Wide Web; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004094414,0.000270811,0.0002929026,0.0001448337,0.0002753346,0.00009692466,0.0013108,0.0001716645,0.0004075264],"category_scores_gemma":[0.0001006373,0.0002656025,0.0001257582,0.0008127768,0.0001758592,0.001908414,0.0006148518,0.0003131983,0.0006533659],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002295528,"about_ca_system_score_gemma":0.0001143394,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002242964,"about_ca_topic_score_gemma":0.000007324833,"domain_scores_codex":[0.9981017,0.000127652,0.0002379486,0.0004901742,0.0003324816,0.0007101104],"domain_scores_gemma":[0.9983476,0.0001687432,0.0001645758,0.0008141233,0.0001752491,0.0003296465],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0007610235,0.00079911,0.01093964,0.0001293512,0.0001308589,0.0001615365,0.00475877,0.00000262503,0.2199801,0.3609523,0.04931689,0.3520678],"study_design_scores_gemma":[0.0008196384,0.0003112134,0.01120855,0.00007410465,0.00003699061,0.0001280772,0.0001037086,0.000434237,0.4328153,0.003227249,0.5498354,0.001005487],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03439207,0.001707925,0.9355472,0.0005206577,0.0004433696,0.0003456524,0.00002000648,0.001053267,0.02596986],"genre_scores_gemma":[0.9520501,0.0002871244,0.03182779,0.0002539201,0.000104597,8.286381e-7,0.000007254025,0.00001619618,0.01545215],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.917658,"threshold_uncertainty_score":0.9999796,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03678406851436043,"score_gpt":0.2599598306261263,"score_spread":0.2231757621117658,"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."}}