{"id":"W2182362006","doi":"","title":"Related Entity Finding: University of Waterloo at TREC 2010 Entity Track.","year":2010,"lang":"en","type":"article","venue":"","topic":"Topic Modeling","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Track (disk drive); Information retrieval; Natural language processing","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00026575,0.00008182548,0.0001255968,0.00006860136,0.0001252355,0.00002828702,0.000749794,0.0001163954,0.0009502721],"category_scores_gemma":[0.00001811264,0.00007957393,0.00007870547,0.0001510819,0.00005737637,0.0004260652,0.000385,0.00021311,0.0001722665],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003170693,"about_ca_system_score_gemma":0.00003461642,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001340941,"about_ca_topic_score_gemma":0.002510111,"domain_scores_codex":[0.9991475,0.00003184891,0.0001478601,0.0003086671,0.0001767926,0.0001873648],"domain_scores_gemma":[0.9991592,0.00003000442,0.00007524247,0.0005954042,0.00005630728,0.00008386702],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005084961,0.0008715009,0.1796618,0.0001206558,0.0001862271,0.0001543611,0.01819003,0.0005272186,0.3806064,0.326601,0.01302989,0.07999999],"study_design_scores_gemma":[0.004120175,0.0002115192,0.2062291,0.00004929483,0.00009270771,0.0001057975,0.0003547882,0.5284328,0.1992654,0.02043439,0.03920715,0.001496894],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9351782,0.000004409459,0.05662047,0.0004317485,0.0009311125,0.00006978616,0.000001572775,0.0001314322,0.006631215],"genre_scores_gemma":[0.9318031,0.000004327296,0.02662694,0.00001577129,0.00001467084,1.004764e-7,0.000001843202,0.000003200038,0.04153003],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5279056,"threshold_uncertainty_score":0.999963,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0149570952927184,"score_gpt":0.1990470455395193,"score_spread":0.1840899502468009,"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."}}