{"id":"W4288037704","doi":"10.1007/s13563-022-00333-3","title":"SQUIDs for magnetic and electromagnetic methods in mineral exploration","year":2022,"lang":"en","type":"article","venue":"Mineral Economics","topic":"Atomic and Subatomic Physics Research","field":"Physics and Astronomy","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"Iron Ore Company (Canada)","funders":"Leibniz-Gemeinschaft; Universität zu Köln; Natural Sciences and Engineering Research Council of Canada; Westfälische Wilhelms-Universität Münster; Leibniz-Institut für Angewandte Geophysik","keywords":"Magnetometer; Gradiometer; Algorithm; Squid; Computer science; Physics; Nuclear magnetic resonance; Magnetic field; Quantum mechanics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001389515,0.0006115137,0.0004693918,0.0009236293,0.000696764,0.00115674,0.0006927915,0.0009153247,0.01468144],"category_scores_gemma":[0.001402313,0.0003801662,0.0002926541,0.0008352554,0.001048057,0.001419032,0.00149844,0.001320998,0.004305426],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007474836,"about_ca_system_score_gemma":0.0004501677,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000606173,"about_ca_topic_score_gemma":0.001228046,"domain_scores_codex":[0.999198,0.0002709476,0.00004234648,0.0001297927,0.0003145169,0.00004435749],"domain_scores_gemma":[0.9995958,0.0001313171,0.00004111619,0.00007073777,0.000123599,0.00003749166],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004027372,0.00009258716,0.000885263,0.001183567,0.00006048965,0.000321512,0.0003221489,0.001359529,0.412842,0.4278353,0.0273644,0.1273306],"study_design_scores_gemma":[0.0001424217,0.0004022458,0.001149996,0.0003883015,0.00005023215,0.0006155561,0.0001420793,0.0147696,0.2237422,0.09444643,0.6640707,0.00008012329],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04252623,0.05698845,0.6687749,0.009398236,0.005908089,0.0007799008,0.001390339,0.006171983,0.2080619],"genre_scores_gemma":[0.4731377,0.02063225,0.3896337,0.002781759,0.001229469,0.00104824,0.001169118,0.000820977,0.109547],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01468144,"threshold_uncertainty_score":0.04911429,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02733170385492207,"score_gpt":0.3204114366956102,"score_spread":0.2930797328406881,"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."}}