{"id":"W1567900743","doi":"","title":"Remote Predictive Mapping 1. Remote Predictive Mapping (RPM): A Strategy for Geological Mapping of Canada’s North","year":2007,"lang":"en","type":"article","venue":"Geoscience Canada","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Geological Survey of Canada","funders":"","keywords":"Geologic map; Geological survey; Field (mathematics); Remote sensing; Cartography; Geology; Geography; Geophysics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"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":[0.003000131,0.0009633899,0.0003298894,0.005557575,0.004653449,0.005163494,0.003017139,0.0009410367,0.01110859],"category_scores_gemma":[0.004000939,0.0005343599,0.0004302069,0.009449229,0.002426011,0.001937235,0.003003382,0.001268012,0.004037746],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0307417,"about_ca_system_score_gemma":0.1300613,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9649498,"about_ca_topic_score_gemma":0.9732732,"domain_scores_codex":[0.9971534,0.0002969798,0.00006460345,0.0002247848,0.001909846,0.0003504124],"domain_scores_gemma":[0.9944451,0.0001717916,0.0001736112,0.0003017303,0.004549827,0.0003579276],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000401864,0.00003950311,0.006265914,0.0005028028,0.00001859642,0.0004234373,0.003008973,0.00628301,0.002991121,0.07188128,0.3167584,0.5917867],"study_design_scores_gemma":[0.0000122179,0.00002110814,0.009759375,0.0004291357,0.00001628467,0.0001868852,0.002178773,0.003977377,0.001393882,0.006375472,0.9755933,0.00005616022],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"methods","genre_scores_codex":[0.0185005,0.005365856,0.3869832,0.02509618,0.0006486293,0.00246379,0.02610791,0.01120864,0.5236253],"genre_scores_gemma":[0.1533501,0.007187944,0.6180367,0.003762639,0.0001382019,0.0008740634,0.02380991,0.002050038,0.1907904],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.03505015,"threshold_uncertainty_score":0.2230477,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02203237968217729,"score_gpt":0.2158105274115651,"score_spread":0.1937781477293878,"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."}}