{"id":"W6980100710","doi":"","title":"Automated prediction of tailings areas at historic gold mine districts in Nova Scotia using multispectral images and a random forest classifier","year":2024,"lang":"en","type":"article","venue":"Saint Mary's University Institutional Repository (Saint Mary's University)","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Nova scotia; Tailings; Random forest; Multispectral image; Classifier (UML); Multispectral pattern recognition","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004327424,0.0004028981,0.0001921879,0.001450323,0.0003831511,0.0007109017,0.0004748346,0.0003209506,0.0005925504],"category_scores_gemma":[0.001026518,0.0001724709,0.0002513579,0.0008029997,0.000201708,0.0002619734,0.0002976164,0.0001693189,0.0004439641],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001642643,"about_ca_system_score_gemma":0.001603684,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6223572,"about_ca_topic_score_gemma":0.7868446,"domain_scores_codex":[0.9998199,0.00001611715,0.00001056767,0.00005424522,0.00003873213,0.00006034566],"domain_scores_gemma":[0.9993111,0.000134674,0.00008019403,0.00003926936,0.0003706123,0.00006416972],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002944563,0.0001286804,0.8398875,0.0001018647,0.0000839977,0.0005994867,0.0003108716,0.04363142,0.01153517,0.0002069855,0.003669112,0.09955043],"study_design_scores_gemma":[0.00002065309,0.00005671874,0.6604046,0.00005207754,0.00004045809,0.0001229767,0.0008779947,0.3324449,0.004143005,0.0001344149,0.001679723,0.00002250977],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.992808,0.0001401755,0.00349428,0.0000737778,0.00001530422,0.00006233789,0.001645899,0.0002373124,0.001522946],"genre_scores_gemma":[0.9890944,0.00007865438,0.007047189,0.00001814239,0.000004613129,0.00001665233,0.002298165,0.00001602013,0.001426084],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3776428,"threshold_uncertainty_score":0.7597335,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01132326812152842,"score_gpt":0.1861411514936032,"score_spread":0.1748178833720748,"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."}}