{"id":"W4414359804","doi":"10.24963/ijcai.2025/475","title":"Adaptive Deep Learning from Crowds","year":2025,"lang":"en","type":"article","venue":"","topic":"Mobile Crowdsensing and Crowdsourcing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Crowds; Crowdsourcing; Flexibility (engineering); Probabilistic logic; Focus (optics); Deep learning; Annotation; Adaptive learning; Reduction (mathematics)","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":[],"consensus_categories":[],"category_scores_codex":[0.0001471498,0.0001097711,0.0001304109,0.00009017649,0.0002190596,0.0002260823,0.0004396145,0.00005918882,0.00004894599],"category_scores_gemma":[0.0000584034,0.000100635,0.00005853425,0.0003674065,0.00003220077,0.0001932265,0.0002486195,0.000199308,0.0001112585],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003428256,"about_ca_system_score_gemma":0.00004150306,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002806335,"about_ca_topic_score_gemma":0.0000381838,"domain_scores_codex":[0.9990636,0.00006951116,0.0001471068,0.0003643511,0.0001279129,0.0002275768],"domain_scores_gemma":[0.999265,0.0001907114,0.00003555431,0.0003975136,0.00005896725,0.00005225755],"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":[0.00001344332,0.00004883498,0.004442987,0.000007511269,0.00009163277,0.00004127109,0.00166746,0.007214954,0.004270213,0.2421222,0.003268137,0.7368113],"study_design_scores_gemma":[0.0004358352,0.00006010288,0.008873513,0.00008106016,0.00001439933,0.000003889623,0.0004575311,0.9390733,0.01401047,0.01613626,0.02052608,0.0003276273],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01907912,0.0002344128,0.8896834,0.0003983937,0.0003250287,0.00004697083,1.080305e-7,0.0004181055,0.08981442],"genre_scores_gemma":[0.9477179,0.000004966869,0.04531084,0.0005752258,0.00004280695,0.000004174789,8.365163e-7,0.000004860281,0.006338374],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9318583,"threshold_uncertainty_score":0.4103776,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01035939629332343,"score_gpt":0.2206287167555865,"score_spread":0.2102693204622631,"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."}}