{"id":"W4392759594","doi":"10.5194/egusphere-egu24-12771","title":"Hybrid AI permafrost modelling","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Climate change and permafrost","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada; St. Francis Xavier University","funders":"","keywords":"Permafrost; Computer science; Geology; Artificial intelligence; Oceanography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0001833185,0.000610469,0.0005384352,0.0004992816,0.0003687517,0.001247728,0.001903681,0.001145136,0.0108159],"category_scores_gemma":[0.0005559959,0.0003243907,0.001086341,0.0006160121,0.0004738062,0.001051031,0.001169836,0.000919167,0.001469957],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006554364,"about_ca_system_score_gemma":0.0008343216,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0122461,"about_ca_topic_score_gemma":0.01248596,"domain_scores_codex":[0.9998629,0.00001624188,0.000008421659,0.0000402976,0.00004479354,0.00002719587],"domain_scores_gemma":[0.9998429,0.00005757284,0.0000132356,0.00002982035,0.00003995674,0.00001650517],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000368873,0.00002232901,0.0008364408,0.00005614733,0.00004089826,0.00009763203,0.00002996784,0.9728249,0.001165844,0.00885428,0.002084212,0.01395048],"study_design_scores_gemma":[0.000004810899,0.000004738703,0.0001268726,0.000004822411,0.000004315482,0.0000161791,0.000005751669,0.9933281,0.0003254705,0.003528257,0.002646149,0.000004549151],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1112388,0.001307483,0.7803038,0.0009570018,0.0002859608,0.0001556647,0.009794727,0.007807827,0.08814872],"genre_scores_gemma":[0.8374088,0.000681733,0.1300009,0.0003192098,0.00008099354,0.0002776595,0.006474536,0.0006599223,0.0240963],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0122461,"threshold_uncertainty_score":0.03618276,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05746415045169701,"score_gpt":0.2620276595666769,"score_spread":0.2045635091149799,"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."}}