{"id":"W4385158975","doi":"10.22541/essoar.169008320.06546433/v1","title":"Characterizing Offshore Freshened Groundwater Salinity Patterns using Trans-dimensional Bayesian Inversion of Controlled Source Electromagnetic Data: A Case Study from the Canterbury Bight, New Zealand","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Geophysical and Geoelectrical Methods","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; Dalhousie University","funders":"European Commission","keywords":"Geology; Hydrogeology; Submarine pipeline; Groundwater; Inversion (geology); Shore; Salinity; Oceanography; Geotechnical engineering; Seismology; Tectonics","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":[0.0003700097,0.0003772461,0.0002522442,0.0006273665,0.0004542674,0.0006321471,0.00072357,0.0004690152,0.0004417422],"category_scores_gemma":[0.001729032,0.0002402392,0.0003426074,0.0009533651,0.0006878495,0.0003830111,0.0005455041,0.000423826,0.00007354427],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001793598,"about_ca_system_score_gemma":0.001445889,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.5223755,"about_ca_topic_score_gemma":0.6366079,"domain_scores_codex":[0.9998036,0.00003464077,0.00001343556,0.00004376482,0.00006512375,0.00003951636],"domain_scores_gemma":[0.9995491,0.0001529563,0.00008689516,0.00003795141,0.0001353456,0.00003770429],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003013466,0.0004584032,0.5807826,0.0002266836,0.0002016635,0.008654554,0.003576808,0.2920495,0.04153438,0.003114816,0.001715606,0.06738357],"study_design_scores_gemma":[0.0001007215,0.0001177999,0.4278139,0.00004634621,0.00008276016,0.0005060274,0.002302561,0.5610396,0.005240532,0.0008930301,0.001752465,0.000104241],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9957429,0.00002017044,0.002873558,0.0001091624,0.00000193642,0.0000217093,0.0003007763,0.00002636058,0.0009034728],"genre_scores_gemma":[0.9949297,0.00004516487,0.004278198,0.00001198814,0.000002408658,0.00001199241,0.0003686168,0.000009049046,0.0003428762],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5223755,"threshold_uncertainty_score":0.9608746,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06144746342943314,"score_gpt":0.2781286129618729,"score_spread":0.2166811495324397,"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."}}