{"id":"W6948863812","doi":"10.5281/zenodo.11557204","title":"Interpretação de Interações entre Vegetação e Clima com IA Explanável","year":2024,"lang":"pt","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Model Reduction and Neural Networks","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Interpretability; Process (computing); Vegetation (pathology); Information system; Data collection","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.001723595,0.0007063275,0.0004498865,0.0009517069,0.0002996563,0.002562136,0.0006138473,0.0004236192,0.005540551],"category_scores_gemma":[0.01005068,0.0002534235,0.001318938,0.001152645,0.0009159148,0.002298016,0.0009820468,0.001551433,0.0008226952],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000749944,"about_ca_system_score_gemma":0.0003854118,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003942382,"about_ca_topic_score_gemma":0.003700403,"domain_scores_codex":[0.9994455,0.0002254315,0.00003057326,0.0001883086,0.00007389145,0.00003628018],"domain_scores_gemma":[0.9970158,0.001856139,0.0002630672,0.0004458558,0.0003186679,0.0001004571],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001995381,0.000292632,0.1882797,0.002851896,0.001329954,0.001844739,0.01408859,0.1259744,0.09186813,0.1867719,0.02282154,0.3618811],"study_design_scores_gemma":[0.00005794971,0.0001842959,0.1330206,0.0004810056,0.0004462495,0.0005170945,0.003794865,0.5625669,0.0157386,0.252257,0.03079857,0.0001368178],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4327998,0.0021464,0.5053697,0.005589831,0.0007101015,0.0001299305,0.009503423,0.00881066,0.03494022],"genre_scores_gemma":[0.952712,0.0005387321,0.04203543,0.0001728495,0.0001096121,0.00004547096,0.0019604,0.0007295689,0.001695939],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005540551,"threshold_uncertainty_score":0.01853496,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03473094719135498,"score_gpt":0.2809978821863338,"score_spread":0.2462669349949788,"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."}}