{"id":"W4400698351","doi":"10.1016/j.marpetgeo.2024.107004","title":"Paleoenvironment assessment of Irati Formation (Paraná Basin, Brazil) based on the semi-quantification of organic sulfur markers by FTICR-MS","year":2024,"lang":"en","type":"article","venue":"Marine and Petroleum Geology","topic":"Hydrocarbon exploration and reservoir analysis","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Alberta Energy","funders":"Shell Brasil; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Geology; Paleontology; Sulfur; Geochemistry; Structural basin; Mineralogy; Chemistry","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":[0.000141834,0.0001595052,0.0001219974,0.0007486655,0.0003617761,0.0003510433,0.0002075814,0.0001421381,0.0005765128],"category_scores_gemma":[0.0002291474,0.0001469502,0.0001235849,0.0006850244,0.0003904583,0.0001838058,0.0004108548,0.0000998067,0.00008919764],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000518865,"about_ca_system_score_gemma":0.0007430111,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0842234,"about_ca_topic_score_gemma":0.2314885,"domain_scores_codex":[0.9999419,0.000006519923,0.000004674961,0.00001715976,0.00001936842,0.00001040683],"domain_scores_gemma":[0.9999437,0.000006980235,0.00001790534,0.000004979461,0.00002057887,0.00000578875],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000144079,0.00004680484,0.8505521,0.0001190353,0.0001022433,0.0007097477,0.004388901,0.002605892,0.09204634,0.001851311,0.0003289188,0.04710453],"study_design_scores_gemma":[0.000004386935,0.0000252985,0.9929098,0.0000122534,0.00002103834,0.0002297072,0.0008461911,0.001447729,0.001980274,0.0001092797,0.002408305,0.000005660621],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9969066,0.000124318,0.0004262665,0.00002927276,0.000001223292,0.00001053378,0.000288168,0.00001438697,0.002199303],"genre_scores_gemma":[0.9985688,0.0000804751,0.0007861214,0.000005788403,7.910243e-7,0.000006960499,0.000109368,0.000004464855,0.0004370954],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0842234,"threshold_uncertainty_score":0.1674663,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006799687823456534,"score_gpt":0.2139448241285143,"score_spread":0.2071451363050578,"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."}}