{"id":"W2529797925","doi":"10.1081/22020586.2010.12041895","title":"A short user guide for UBC-GIF gravity and magnetic inversions","year":2010,"lang":"en","type":"article","venue":"ASEG Extended Abstracts","topic":"Geophysical and Geoelectrical Methods","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Inversion (geology); Weighting; Potential field; Property (philosophy); Geology; Geophysics; Computer science; Uniqueness; Field (mathematics); Data mining; Data processing; Inverse problem; Algorithm; Seismology; Mathematics; Database","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001144525,0.001939173,0.001198247,0.003543483,0.0008470535,0.001988417,0.002823151,0.001740803,0.5091761],"category_scores_gemma":[0.006287444,0.001082862,0.0009434507,0.004072417,0.0003640165,0.002100092,0.001743109,0.001753826,0.3142737],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006362416,"about_ca_system_score_gemma":0.001076853,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005778424,"about_ca_topic_score_gemma":0.008932807,"domain_scores_codex":[0.9995372,0.00007404616,0.00005436773,0.00005999444,0.0002285675,0.00004587115],"domain_scores_gemma":[0.9976925,0.0008962471,0.00007503025,0.000282959,0.0009419392,0.000111361],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007994313,0.00004385597,0.0003340482,0.0003617282,0.00001635298,0.0001457685,0.0000582774,0.002176147,0.001469577,0.003879425,0.8326911,0.1587438],"study_design_scores_gemma":[0.00006938566,0.00002526477,0.0006667585,0.0001539781,0.000008407399,0.0003187281,0.00005791752,0.0102513,0.001642359,0.007012092,0.9797422,0.00005155871],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002076208,0.002555443,0.5322167,0.001036309,0.002093894,0.001069478,0.1148732,0.178706,0.1653726],"genre_scores_gemma":[0.01274322,0.002731202,0.5744908,0.001672036,0.001134945,0.003153057,0.1449811,0.05841795,0.2006757],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5091761,"threshold_uncertainty_score":0.7001008,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01466811237846248,"score_gpt":0.2600088338679305,"score_spread":0.245340721489468,"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."}}