{"id":"W3103117332","doi":"","title":"Your \"Labrador\" is My \"Dog\": Fine-Grained, or Not.","year":2020,"lang":"en","type":"article","venue":"arXiv (Cornell University)","topic":"Domain Adaptation and Few-Shot Learning","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Leverage (statistics); Intuition; Granularity; Artificial intelligence; Classifier (UML); Single level; Machine learning; Psychology; Cognitive science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001358051,0.0005875744,0.0003039565,0.0006528666,0.001012214,0.002575613,0.0007751716,0.001533055,0.008230156],"category_scores_gemma":[0.009630277,0.000196003,0.000437614,0.0004739142,0.001581898,0.0062597,0.00114879,0.00138993,0.00254987],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001046326,"about_ca_system_score_gemma":0.0004325208,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007312612,"about_ca_topic_score_gemma":0.01008273,"domain_scores_codex":[0.9990766,0.0002328654,0.00003698173,0.0003694928,0.0001525724,0.000131404],"domain_scores_gemma":[0.997779,0.0009942988,0.0002740948,0.0003367041,0.0004128333,0.0002031245],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001406454,0.0001999435,0.1203808,0.001159709,0.0001466228,0.0009522627,0.01990655,0.005028185,0.0481177,0.09494025,0.09320796,0.6145536],"study_design_scores_gemma":[0.00009979971,0.0006247138,0.1446741,0.001223843,0.000309043,0.005164369,0.04506015,0.1685807,0.03550932,0.2741527,0.3241782,0.0004230917],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5471721,0.003405768,0.2869639,0.01352004,0.0009338184,0.0004585586,0.002904179,0.004221215,0.1404204],"genre_scores_gemma":[0.9293197,0.0004222987,0.05770934,0.00129994,0.00007533283,0.00007483531,0.001079262,0.0002651146,0.009754141],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008230156,"threshold_uncertainty_score":0.02753258,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1307720786565493,"score_gpt":0.2032991229909423,"score_spread":0.07252704433439303,"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."}}