{"id":"W2594164625","doi":"10.1145/3025171.3025208","title":"Label-and-Learn","year":2017,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Leverage (statistics); Classifier (UML); Machine learning; Artificial intelligence; Software; Visualization; Data science; Human–computer interaction","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":[0.005834991,0.002732354,0.001174082,0.001999685,0.0007763706,0.003349852,0.002803816,0.002670004,0.04325034],"category_scores_gemma":[0.03293608,0.0008180069,0.001167264,0.001016923,0.0009710435,0.006459923,0.004966808,0.003268582,0.01121849],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007139692,"about_ca_system_score_gemma":0.0009191131,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001303868,"about_ca_topic_score_gemma":0.002334135,"domain_scores_codex":[0.9977701,0.0009143948,0.0001747559,0.0004205626,0.0005522021,0.0001680186],"domain_scores_gemma":[0.9709387,0.01904699,0.001457961,0.005291185,0.002492754,0.0007723661],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002735107,0.001426217,0.01211664,0.001845743,0.0001836988,0.001140762,0.006091232,0.01008492,0.01283271,0.0368329,0.4165265,0.4981835],"study_design_scores_gemma":[0.0009768578,0.0008105332,0.008955272,0.001147575,0.0001289185,0.001249266,0.001611419,0.340391,0.05610641,0.165734,0.4224605,0.0004282659],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.02476636,0.0006218937,0.6815521,0.004404528,0.0006763287,0.0008035781,0.009709443,0.2599755,0.01749029],"genre_scores_gemma":[0.1996894,0.000943021,0.7222996,0.002962088,0.0004711601,0.002632435,0.01377337,0.03451491,0.02271411],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.04325034,"threshold_uncertainty_score":0.1446868,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04749049072780054,"score_gpt":0.3425766233070547,"score_spread":0.2950861325792541,"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."}}