{"id":"W3008638314","doi":"10.1016/j.ijar.2020.02.003","title":"Label distribution learning: A local collaborative mechanism","year":2020,"lang":"en","type":"article","venue":"International Journal of Approximate Reasoning","topic":"Text and Document Classification Technologies","field":"Computer Science","cited_by":41,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"National Natural Science Foundation of China","keywords":"Robustness (evolution); Ambiguity; Computer science; Artificial intelligence; Machine learning; Feature learning; Representation (politics); Pattern recognition (psychology)","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":[0.01123617,0.001230187,0.002622547,0.003092006,0.003619496,0.004811798,0.009424263,0.004842258,0.011719],"category_scores_gemma":[0.02775939,0.001037653,0.001937623,0.004701944,0.002437192,0.009820425,0.01242648,0.00408987,0.003638513],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001918971,"about_ca_system_score_gemma":0.002964992,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004482917,"about_ca_topic_score_gemma":0.007033485,"domain_scores_codex":[0.991616,0.002773653,0.0004938073,0.001977005,0.002586063,0.0005535596],"domain_scores_gemma":[0.9773299,0.008463179,0.001055975,0.009253772,0.002993935,0.0009031407],"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":[0.001585966,0.001535808,0.004174915,0.0002805904,0.0003520279,0.0002177737,0.0008456961,0.06008149,0.01283623,0.07498785,0.01741615,0.8256854],"study_design_scores_gemma":[0.0002357703,0.0001871297,0.0006243092,0.00003528003,0.0001463094,0.0001997961,0.0001639663,0.8668132,0.01424122,0.1095221,0.007769173,0.00006170964],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006738469,0.0001444155,0.989838,0.000360709,0.00005443379,0.00009991998,0.00008652839,0.001248868,0.001428705],"genre_scores_gemma":[0.3171343,0.0002127832,0.6692164,0.0005201558,0.0003503738,0.0004141781,0.0006568087,0.0004442349,0.01105076],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.011719,"threshold_uncertainty_score":0.05942327,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0166668925147492,"score_gpt":0.2669003154745818,"score_spread":0.2502334229598325,"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."}}