{"id":"W3108140760","doi":"10.1190/tle39120883.1","title":"Using geodetic data in geothermal areas","year":2020,"lang":"en","type":"article","venue":"The Leading Edge","topic":"Geophysical Methods and Applications","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Geodetic datum; Geothermal gradient; Deformation monitoring; Geology; Interferometric synthetic aperture radar; Remote sensing; Geodesy; Field (mathematics); Geothermal energy; Synthetic aperture radar; Deformation (meteorology); Seismology; Geophysics","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":[0.001203506,0.0003638536,0.000304819,0.002660217,0.0001888023,0.0021319,0.0004293912,0.0005034567,0.001320131],"category_scores_gemma":[0.003059752,0.0001534089,0.0002031488,0.005938195,0.0003977561,0.001374028,0.0007851031,0.0004581908,0.0005744562],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004154841,"about_ca_system_score_gemma":0.0004603961,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006055817,"about_ca_topic_score_gemma":0.01093084,"domain_scores_codex":[0.9992256,0.0003094714,0.00006098166,0.0001526234,0.0002206613,0.00003067825],"domain_scores_gemma":[0.998713,0.0004523014,0.0002548581,0.0001498122,0.0003872364,0.00004269037],"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":[0.000112191,0.0000804759,0.1260054,0.001323036,0.0002473373,0.0004483678,0.0005326092,0.03111403,0.008565076,0.03358639,0.01970587,0.7782792],"study_design_scores_gemma":[0.00006127335,0.0001834688,0.2437732,0.003425807,0.0003038733,0.001058623,0.003462235,0.1251663,0.02519314,0.0961375,0.5010333,0.0002012865],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3309893,0.09617855,0.3947753,0.01453292,0.002098728,0.0002816738,0.02175984,0.002146663,0.137237],"genre_scores_gemma":[0.8651844,0.02645838,0.0987863,0.000686057,0.0005159233,0.00006862438,0.004323156,0.0000638695,0.003913322],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006055817,"threshold_uncertainty_score":0.01204109,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1594074066558642,"score_gpt":0.3340051936914423,"score_spread":0.1745977870355781,"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."}}