{"id":"W2884906841","doi":"","title":"St. Lawrence Lowlands bottom-hole temperatures: various correction methods.","year":2014,"lang":"en","type":"article","venue":"","topic":"Geothermal Energy Systems and Applications","field":"Energy","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Geothermal gradient; Structural basin; Geology; Sedimentary rock; Sedimentary basin; Hydrology (agriculture); Mineralogy; Environmental science; Geomorphology; Geochemistry; Paleontology; Geotechnical engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008568256,0.0005376729,0.0002054887,0.001505292,0.0005874215,0.0006070244,0.0008314422,0.0002940799,0.004576548],"category_scores_gemma":[0.002432636,0.0003404431,0.0003296463,0.002260326,0.0001678093,0.000340585,0.0003912322,0.000323373,0.002294898],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001791368,"about_ca_system_score_gemma":0.001802922,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2436982,"about_ca_topic_score_gemma":0.5023735,"domain_scores_codex":[0.9993351,0.00006087991,0.00003998371,0.0001283837,0.0003937811,0.00004181187],"domain_scores_gemma":[0.9987614,0.0000796004,0.0002075246,0.0001360814,0.000781983,0.00003336732],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005378893,0.0001387537,0.3539861,0.0006231439,0.0002118776,0.0003700511,0.00119201,0.02489189,0.02646016,0.001993406,0.05260041,0.5369945],"study_design_scores_gemma":[0.0001292734,0.00011661,0.6963888,0.0001484329,0.000175461,0.0003399896,0.0007395963,0.1049853,0.04745222,0.0007549253,0.1485947,0.0001745954],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.5772002,0.003848276,0.2673027,0.0007766531,0.001200103,0.0008383699,0.07914836,0.02250491,0.04718046],"genre_scores_gemma":[0.6934031,0.0007955816,0.2523568,0.0001171585,0.00004865693,0.0003702799,0.02143786,0.002354912,0.02911573],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.2436982,"threshold_uncertainty_score":0.4845594,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0102565250033912,"score_gpt":0.2676442381199,"score_spread":0.2573877131165088,"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."}}