{"id":"W7073735857","doi":"","title":"Forward modelling and inversion of geophysical magnetic data","year":2003,"lang":"en","type":"other","venue":"cIRcle (University of British Columbia)","topic":"Prenatal Screening and Diagnostics","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Unexploded ordnance; Discretization; Magnetic field; Inverse problem; Magnetometer; Amplitude; Inversion (geology); Magnetic susceptibility; Constant (computer programming)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":{"n_in":0,"stratum":"fund_new","weight":1678.9,"opus":{"tier":"OUT","genre":"empirical","about_ca":false,"confidence":"high","reason":"Forward modeling and inversion of magnetic data; a geophysics methods contribution in its own domain."},"gpt":{"tier":"OUT","genre":"empirical","about_ca":false,"confidence":"high","reason":"The work develops geophysical modelling and inversion methods for Earth data, not methods of research generally."},"grok":{"tier":"OUT","genre":"empirical","about_ca":false,"confidence":"high","reason":"Geophysical inversion of magnetic data for subsurface susceptibility; domain method development, not research methods."}},"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004689405,0.0005088392,0.000503922,0.0004591433,0.0002893939,0.000906897,0.0009676412,0.001031477,0.002124935],"category_scores_gemma":[0.00197603,0.0004685116,0.0006849326,0.0004619054,0.0004943687,0.0009233415,0.0008305546,0.0009332867,0.000750589],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004018825,"about_ca_system_score_gemma":0.001287383,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00945702,"about_ca_topic_score_gemma":0.00701803,"domain_scores_codex":[0.9998529,0.00002553251,0.00001054004,0.00002628343,0.00006909502,0.00001569121],"domain_scores_gemma":[0.9994423,0.0002747128,0.00004568306,0.00006494432,0.0001560832,0.00001635512],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002106955,0.00001354167,0.0004457711,0.00008214545,0.00001453269,0.00008182847,0.00007162872,0.9594221,0.007051637,0.005996178,0.0004282124,0.02637137],"study_design_scores_gemma":[0.00000302305,0.000005712877,0.0000714955,0.000005718721,0.000001756683,0.00001761367,0.00001057861,0.9958445,0.001448571,0.00162373,0.0009625627,0.000004671456],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01513495,0.00008558427,0.980787,0.0001267383,0.00004490258,0.00004692601,0.0002013611,0.0008274438,0.002745103],"genre_scores_gemma":[0.4310772,0.0004561447,0.5582264,0.0001120824,0.00004440766,0.0002755564,0.0009637259,0.0002674267,0.008577067],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00945702,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0166533257961689,"score_gpt":0.1938003754413387,"score_spread":0.1771470496451698,"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."}}