{"id":"W4417538516","doi":"10.48550/arxiv.2506.16531","title":"How Hard Is Snow? A Paired Domain Adaptation Dataset for Clear and Snowy Weather: CADC+","year":2025,"lang":"en","type":"preprint","venue":"ArXiv.org","topic":"Advanced Neural Network Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Domain adaptation; Snow; Domain (mathematical analysis); Sequence (biology); Noise (video); Object detection; Object (grammar); Point (geometry)","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002067781,0.0003256173,0.0003360574,0.0001055626,0.0002623888,0.0002578432,0.001117036,0.000215038,0.000003703921],"category_scores_gemma":[0.00007368941,0.0003356093,0.0001036071,0.000275554,0.00008327512,0.0004011704,0.001396681,0.0003719107,0.00001992388],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007063475,"about_ca_system_score_gemma":0.0001139829,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004005537,"about_ca_topic_score_gemma":0.00005342667,"domain_scores_codex":[0.9979116,0.00007650643,0.0002899316,0.001175119,0.0001940216,0.0003527873],"domain_scores_gemma":[0.9976116,0.0003119883,0.0002643974,0.001583671,0.0001080552,0.0001202619],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004145043,0.000693234,0.02864765,0.001686477,0.0009105871,0.00006573307,0.0114949,0.007694343,0.003417012,0.1067761,0.5307161,0.3074833],"study_design_scores_gemma":[0.001364539,0.0001832159,0.01868706,0.0003944917,0.0001243989,0.00001521919,0.0002276186,0.1291742,0.001977888,0.07707193,0.7694968,0.001282635],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02173454,0.0004150879,0.9548205,0.01802405,0.0003700029,0.001447518,0.0028926,0.0002267257,0.00006900435],"genre_scores_gemma":[0.2589658,0.001301062,0.7177342,0.006648702,0.0007718538,0.002699683,0.006095542,0.0000988699,0.005684348],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3062007,"threshold_uncertainty_score":0.9999096,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.077045986734562,"score_gpt":0.2940337026000955,"score_spread":0.2169877158655335,"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."}}