{"id":"W852997015","doi":"10.1007/978-3-319-18356-5_7","title":"Budget-Driven Big Data Classification","year":2015,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Bandit Algorithms Research","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Computer science; Class (philosophy); Big data; Process (computing); Machine learning; Artificial intelligence; Set (abstract data type); Data set; Training set; Support vector machine; Data mining; Scale (ratio); Programming language","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","open_science","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.006387269,0.0004636925,0.0006620023,0.001749006,0.0002864691,0.0009651834,0.01158126,0.0003901592,0.0001468402],"category_scores_gemma":[0.004731281,0.0003520758,0.0000842487,0.001542287,0.001886123,0.001007631,0.00490827,0.001189861,0.0009167627],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005139626,"about_ca_system_score_gemma":0.001708696,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001817564,"about_ca_topic_score_gemma":0.000226668,"domain_scores_codex":[0.9889258,0.0001079187,0.0009556155,0.002979599,0.006279323,0.0007517972],"domain_scores_gemma":[0.9897659,0.00232896,0.0005125392,0.005509341,0.001518026,0.0003652441],"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":[0.000009842054,0.00001633477,0.00005218604,0.000003992858,0.000004589896,0.0000416115,0.0001343851,0.0194934,0.00004417182,0.0004879197,0.00126036,0.9784512],"study_design_scores_gemma":[0.00022438,0.0000908125,0.0002210109,0.00007654785,0.00000472564,0.00003164239,9.058743e-7,0.5864283,0.00007255978,0.323768,0.08864967,0.0004313945],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00001238015,0.0005729977,0.9891167,0.001255092,0.002971277,0.0004377452,0.0001026756,0.00007122196,0.005459854],"genre_scores_gemma":[0.2100473,0.0002950142,0.7491332,0.001940415,0.01182027,0.00004068568,0.0005444791,0.0002863662,0.02589219],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9780198,"threshold_uncertainty_score":0.9998931,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3721219145682331,"score_gpt":0.4431382603684922,"score_spread":0.07101634580025912,"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."}}