{"id":"W6963225870","doi":"10.20383/103.01137","title":"High-Resolution Historical and Pseudo Global Warming (PGW) Simulations for northeastern North America Catalogue (HR-HiPNENAC), V1","year":2025,"lang":"en","type":"dataset","venue":"Open MIND","topic":"","field":"","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Climate model; Grid; Climate change; Climate simulation; Global warming; General Circulation Model; Domain (mathematical analysis); Numerical weather prediction; Atmospheric model","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","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002852921,0.0008247053,0.001208713,0.0003323737,0.0006574803,0.0004597555,0.001594424,0.0005115622,0.0002881952],"category_scores_gemma":[0.0004912514,0.0008818287,0.0002017669,0.0008622209,0.000197081,0.0005060757,0.00143086,0.000518165,0.0009774085],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002829627,"about_ca_system_score_gemma":0.0008395799,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.02602074,"about_ca_topic_score_gemma":0.09823047,"domain_scores_codex":[0.9957525,0.0002073494,0.0009864328,0.00160215,0.0005914922,0.0008600838],"domain_scores_gemma":[0.9966807,0.0004001696,0.0007831646,0.001449821,0.0003066377,0.0003794827],"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":[0.0003577386,0.0003051554,0.0003931232,0.000100675,0.000218161,0.00003332699,0.00006015239,0.001419715,0.000007553889,0.000001820441,0.9814871,0.01561549],"study_design_scores_gemma":[0.001524052,0.0001913586,0.0003121742,0.0001544964,0.0009106715,0.00002145561,0.00002998583,0.001967083,0.000003847085,0.00001759234,0.9940112,0.0008561297],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00458135,0.0003285367,0.0005382881,0.0001939628,0.0009581328,0.002575989,0.990731,0.00001356507,0.00007919042],"genre_scores_gemma":[0.001624087,0.00003033694,0.006260776,0.00007091744,0.0004130665,0.0002123159,0.9899705,0.00006104117,0.001356974],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07220974,"threshold_uncertainty_score":0.9998004,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03289537591280364,"score_gpt":0.3117583459139275,"score_spread":0.2788629700011239,"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."}}