{"id":"W2538950009","doi":"10.1130/ges01326.1","title":"An approach for automated lithological classification of point clouds","year":2016,"lang":"en","type":"article","venue":"Geosphere","topic":"3D Surveying and Cultural Heritage","field":"Earth and Planetary Sciences","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Suncor Energy (Canada); Queen's University","funders":"Suncor Energy Incorporated","keywords":"Geology; Point cloud; Point (geometry); Mineralogy; Artificial intelligence; Geometry; Computer science; Mathematics","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":[0.0008278989,0.0005357591,0.0006672458,0.00239527,0.0007966396,0.001588175,0.001616625,0.001017702,0.001487508],"category_scores_gemma":[0.002038429,0.0004561683,0.0009857307,0.001747872,0.0005434538,0.001143639,0.00131175,0.001099593,0.001504848],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007186267,"about_ca_system_score_gemma":0.001084656,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004915845,"about_ca_topic_score_gemma":0.006304401,"domain_scores_codex":[0.9988149,0.0001349078,0.0000939116,0.0002982598,0.0005505733,0.0001073564],"domain_scores_gemma":[0.9990176,0.0001773281,0.00008814473,0.000207992,0.0004762295,0.0000326368],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005568021,0.0001334881,0.002502618,0.00006597776,0.00004933901,0.00007129238,0.00008685061,0.04687467,0.01902152,0.003356021,0.002888527,0.9248941],"study_design_scores_gemma":[0.000009043269,0.00004155482,0.002327819,0.00001808091,0.000009903032,0.0001212032,0.0000739465,0.9749265,0.01217537,0.0045317,0.005744764,0.0000200438],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00926934,0.0000930522,0.9882758,0.0000816523,0.00003040069,0.00008613853,0.0001553566,0.00140504,0.0006031033],"genre_scores_gemma":[0.1206666,0.0001002494,0.8764279,0.00008235569,0.00004143507,0.000183123,0.0006781971,0.00007837897,0.001741711],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004915845,"threshold_uncertainty_score":0.009774446,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03739116753454855,"score_gpt":0.2558484134468864,"score_spread":0.2184572459123378,"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."}}