{"id":"W2991351258","doi":"","title":"Using Fuzzy Logic for the Inference of the Holocene Land Uplift in the Hudson-Bay Region Based on Sea-Level Indicators","year":2005,"lang":"en","type":"article","venue":"Publication Database GFZ (GFZ German Research Centre for Geosciences)","topic":"Geology and Paleoclimatology Research","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Bay; Holocene; Fuzzy logic; Geology; Inference; Physical geography; Oceanography; Computer science; Artificial intelligence; Geography","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.008174066,0.0001676663,0.0001847157,0.0005345478,0.00139862,0.0001587892,0.002360255,0.0001306738,0.0002190802],"category_scores_gemma":[0.003566927,0.00008477337,0.00009487935,0.002255653,0.001419458,0.0004250828,0.0001042204,0.00058414,0.00003402068],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001399685,"about_ca_system_score_gemma":0.0006657409,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001027574,"about_ca_topic_score_gemma":0.007818674,"domain_scores_codex":[0.9960539,0.0008914659,0.0003916548,0.0005656079,0.001102292,0.0009950966],"domain_scores_gemma":[0.9925204,0.005698639,0.0002162771,0.001008103,0.0004122008,0.0001443711],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000114452,0.0001082645,0.9873865,0.00004151561,0.000006004092,9.945774e-7,0.0002538045,0.001220495,0.000002252919,0.00297769,0.00354936,0.004338614],"study_design_scores_gemma":[0.0007258655,0.0001204279,0.7449364,0.00004102689,0.00001245994,0.00001100626,0.0004109207,0.2361882,0.0001287964,0.00107616,0.01619904,0.0001496937],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8711799,0.00039317,0.004215077,0.1138282,0.0003109032,0.004500126,0.004010273,0.00003458636,0.001527742],"genre_scores_gemma":[0.9967071,0.00005870097,0.0008553166,0.001092315,0.00008575944,0.00007165255,0.0009727144,0.000004318297,0.0001520985],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2424501,"threshold_uncertainty_score":0.9999014,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1251482321018,"score_gpt":0.3664834734835061,"score_spread":0.241335241381706,"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."}}