{"id":"W4207085285","doi":"10.5260/chara.23.3.26","title":"Geoscan","year":2022,"lang":"en","type":"article","venue":"The Charleston Advisor","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Natural resource; Government (linguistics); Library science; Service (business); Geological survey; Computer science; Business; World Wide Web; Environmental resource management; Database; Political science; Geology; Environmental science","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001883097,0.001625697,0.0017844,0.006008751,0.003171939,0.00907354,0.005012857,0.001407161,0.2594205],"category_scores_gemma":[0.006659439,0.0009708479,0.0009220158,0.01317512,0.0008468009,0.004835549,0.003547366,0.00198016,0.2399227],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007439991,"about_ca_system_score_gemma":0.02644881,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.6256858,"about_ca_topic_score_gemma":0.6579967,"domain_scores_codex":[0.9975247,0.000178873,0.0001397791,0.0004583672,0.001350281,0.0003481364],"domain_scores_gemma":[0.9934691,0.000394015,0.0001704697,0.0009658227,0.004381056,0.0006194495],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006563184,0.00001052717,0.0004124467,0.0001012133,0.00001644057,0.000021811,0.00005800236,0.0002442627,0.0001423675,0.004287068,0.9713959,0.02324424],"study_design_scores_gemma":[0.00002099874,0.000003222531,0.0004502165,0.00006272714,0.00001279634,0.00001975816,0.00008771624,0.0007025917,0.0002041174,0.001689908,0.9967214,0.00002463181],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.001029775,0.001028277,0.0172239,0.001756373,0.0006614958,0.0003223622,0.6471683,0.07750528,0.2533043],"genre_scores_gemma":[0.006930725,0.00192575,0.03021442,0.001005471,0.0001465752,0.0003453054,0.807342,0.01525521,0.1368345],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.7405795,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01313446539174854,"score_gpt":0.2058591910679814,"score_spread":0.1927247256762329,"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."}}