{"id":"W4412875458","doi":"10.1145/3711896.3736830","title":"Adaptive Conformal Prediction Intervals for Invariant Learning","year":2025,"lang":"en","type":"article","venue":"","topic":"Domain Adaptation and Few-Shot Learning","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; University of Alberta","keywords":"Invariant (physics); Conformal map; Computer science; Artificial intelligence; Mathematics; Mathematical analysis","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0004369628,0.00007798694,0.00009856735,0.0001249056,0.0001852794,0.0001561261,0.0002792086,0.00004467041,0.0000384756],"category_scores_gemma":[0.000152727,0.00007102531,0.00005730567,0.0002214561,0.00002024532,0.0005008933,0.0001199894,0.0001310591,0.00003124625],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003298027,"about_ca_system_score_gemma":0.00007735086,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001121548,"about_ca_topic_score_gemma":0.00000424738,"domain_scores_codex":[0.9992643,0.00005033877,0.0002017406,0.0002045091,0.0001030378,0.0001760999],"domain_scores_gemma":[0.9994898,0.0001693899,0.00006106579,0.0001364151,0.0001011532,0.00004212845],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000266181,0.00001705055,0.0002879662,0.00001058998,0.00002959826,8.163559e-7,0.0008962859,0.003047435,0.0002189612,0.9134869,0.002075694,0.07990206],"study_design_scores_gemma":[0.000589575,0.0001601935,0.001551183,0.00003035013,0.000005230358,0.000002209264,0.0005499611,0.9230363,0.0005763664,0.003429935,0.06998481,0.00008383665],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0002703604,0.00001852815,0.8957227,0.0006091858,0.0003489175,0.0001879213,7.925206e-7,0.0002600168,0.1025815],"genre_scores_gemma":[0.8613883,0.000004987831,0.1170569,0.001287661,0.00003922843,0.00005421371,0.000006631683,0.00000501629,0.02015708],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9199889,"threshold_uncertainty_score":0.2896328,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02320253054774044,"score_gpt":0.2662651193575236,"score_spread":0.2430625888097831,"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."}}