{"id":"W2104551679","doi":"10.1190/1.1543195","title":"Okak Bay AMT data-set case study: Lessons in dimensionality and scale","year":2003,"lang":"en","type":"article","venue":"Geophysics","topic":"Geophysical and Geoelectrical Methods","field":"Earth and Planetary Sciences","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"Geological Survey of Canada","funders":"","keywords":"Curse of dimensionality; Geology; Bay; Scale (ratio); Magnetotellurics; Consistency (knowledge bases); Geophysics; Data set; Drilling; Remote sensing; Mineralogy; Oceanography; Computer science; Cartography; Materials science; Geography; Physics; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005607025,0.0001538513,0.0002570513,0.00003568638,0.0001555916,0.00004443922,0.0001733702,0.00004793608,0.0001527087],"category_scores_gemma":[0.00009905061,0.0001220087,0.00002728142,0.0005049633,0.00007591826,0.0002120713,0.00004758194,0.0002353529,0.0001157446],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000002521791,"about_ca_system_score_gemma":0.00003998536,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009955198,"about_ca_topic_score_gemma":0.008192356,"domain_scores_codex":[0.9983459,0.0003828752,0.0001939277,0.0005056636,0.0002223317,0.0003492901],"domain_scores_gemma":[0.9988782,0.0004126355,0.00004405675,0.0004769233,0.00002555815,0.0001626541],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00004294745,0.0008502603,0.4891397,0.00003279843,0.00003944936,0.001517761,0.0009583472,0.0003081935,0.00004068654,0.0006602125,0.000312927,0.5060967],"study_design_scores_gemma":[0.0005058139,0.0002704717,0.9691078,0.000005599813,0.00003099821,0.0001423386,0.0007257545,0.002760772,0.00003889465,0.02462742,0.001511323,0.0002727809],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983776,0.0001271535,0.00004808408,0.0001583666,0.0001265088,0.0001954327,0.0001316019,0.00002071028,0.0008145032],"genre_scores_gemma":[0.9983386,0.000009159504,0.001246886,0.0001530686,0.00005902602,0.000001661875,0.00006570989,0.000003194527,0.0001226273],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5058239,"threshold_uncertainty_score":0.9966376,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07216115340155518,"score_gpt":0.3175779359526504,"score_spread":0.2454167825510952,"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."}}