{"id":"W3096564232","doi":"10.1130/abs/2020am-355079","title":"FACTORS INVOLVED IN THE BIOGEOGRAPHIC DISTRIBUTION OF MICROBIAL DIVERSITY IN SUBSURFACE WATER OF THE LAURENTIDES REGION, QUEBEC","year":2020,"lang":"en","type":"article","venue":"Abstracts with programs - Geological Society of America","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Diversity (politics); Distribution (mathematics); Geography; Environmental science; Ecology; Biology; Mathematics","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":[0.0002813779,0.0001824243,0.000273464,0.001147835,0.001875826,0.001267256,0.0005725435,0.000266487,0.002365202],"category_scores_gemma":[0.0009904112,0.0001693883,0.0002172244,0.002017424,0.0008159986,0.0003588185,0.0004499783,0.0003129459,0.0001611621],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01393534,"about_ca_system_score_gemma":0.01071145,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9891506,"about_ca_topic_score_gemma":0.9951748,"domain_scores_codex":[0.9997271,0.0000286135,0.00001496223,0.00006492715,0.00005508116,0.0001092637],"domain_scores_gemma":[0.999035,0.0001361872,0.0001766898,0.00001801539,0.0004595266,0.0001744468],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001113387,0.00003137481,0.986948,0.00005089965,0.00005572693,0.000137256,0.001222983,0.0005487825,0.003299607,0.000243457,0.0006976834,0.006652835],"study_design_scores_gemma":[0.00000279066,0.000006991079,0.9980419,0.00001255144,0.000006242033,0.00001801492,0.001046692,0.0002748998,0.0001021957,0.00001438774,0.0004687881,0.000004469522],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9958658,0.0002786241,0.0001193831,0.0002271482,0.000004890849,0.00001543889,0.00139468,0.000007518776,0.002086454],"genre_scores_gemma":[0.9984725,0.0001474229,0.0001037081,0.00004185378,0.00000285797,0.000007359608,0.0004143491,0.000002832745,0.0008071053],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01393534,"threshold_uncertainty_score":0.1011084,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03354247556643063,"score_gpt":0.2118413793228083,"score_spread":0.1782989037563776,"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."}}