{"id":"W1589509960","doi":"10.1002/9781118165409.ch5","title":"Seeing Frequency Data","year":2006,"lang":"en","type":"other","venue":"Wiley series in probability and statistics","topic":"Statistical and numerical algorithms","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Frequency distribution; Computer science; Mathematics; Statistics","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":[0.0003414413,0.0003765281,0.0006762075,0.00008501911,0.00006113511,0.00005565621,0.0004276455,0.0003082419,0.0006903882],"category_scores_gemma":[0.001816257,0.0003349773,0.00002180044,0.0001759357,0.0005931705,0.00008998484,0.0003752073,0.0004091296,0.00001457351],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004970074,"about_ca_system_score_gemma":0.00007415166,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001273956,"about_ca_topic_score_gemma":0.006036739,"domain_scores_codex":[0.997849,0.0001439415,0.000585768,0.0007319572,0.0002991994,0.000390174],"domain_scores_gemma":[0.9978729,0.0008050899,0.0001970545,0.0009784274,0.00003932152,0.0001071918],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00001460816,0.0001850593,0.0008882583,0.001432098,0.00003112867,0.000075024,0.00005536159,2.052978e-7,4.786171e-7,0.4572938,0.5157763,0.02424766],"study_design_scores_gemma":[0.0002053642,0.00007385186,0.0002106437,0.0003772022,0.00005250867,0.00001185171,0.00001506252,0.0004509118,5.629016e-7,0.866631,0.1315901,0.0003809539],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00002905187,0.003755065,0.6151736,0.0002574359,0.00088999,0.001596743,0.04276272,0.000525703,0.3350097],"genre_scores_gemma":[0.00002305202,0.0005893786,0.9206212,0.00003826019,0.000194599,0.00003417657,0.001100591,0.0002209883,0.07717776],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4093372,"threshold_uncertainty_score":0.9999102,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06208439900508019,"score_gpt":0.3141534234756144,"score_spread":0.2520690244705343,"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."}}