{"id":"W3032112355","doi":"10.4095/321092","title":"Machine learning applied to geoscience: Geo-referenced character recognition","year":2020,"lang":"en","type":"report","venue":"","topic":"Geological Modeling and Analysis","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Character (mathematics); Computer science; Character recognition; Geology; Earth science; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"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":[0.001902767,0.0009199099,0.0006447247,0.002322717,0.0004889018,0.002286326,0.001346285,0.0010128,0.008923065],"category_scores_gemma":[0.008078802,0.0003250188,0.0004478506,0.00511394,0.0007468264,0.001800328,0.001422453,0.001453368,0.006586595],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008496196,"about_ca_system_score_gemma":0.001564182,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005627711,"about_ca_topic_score_gemma":0.004077669,"domain_scores_codex":[0.9971755,0.0006458588,0.0001696475,0.0005323457,0.001328783,0.0001479119],"domain_scores_gemma":[0.9964634,0.00116664,0.0002362235,0.000642915,0.001325276,0.0001654975],"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":[0.0000744167,0.0001934542,0.004129068,0.000583289,0.00007592599,0.0001737975,0.0001380526,0.03888408,0.006553587,0.01312044,0.06271003,0.8733639],"study_design_scores_gemma":[0.00003413183,0.0001145803,0.0108231,0.000455032,0.00004450326,0.0006795882,0.0002520907,0.6050147,0.04685963,0.06679726,0.2688086,0.0001167077],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01392839,0.003632451,0.9346839,0.001868721,0.000964368,0.0003772668,0.00572906,0.01344416,0.02537157],"genre_scores_gemma":[0.1984266,0.005276638,0.7474239,0.0005837047,0.0005872147,0.0006612929,0.01738557,0.001663269,0.02799184],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008923065,"threshold_uncertainty_score":0.0298506,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07891648579214025,"score_gpt":0.251382731731966,"score_spread":0.1724662459398257,"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."}}