{"id":"W4285195205","doi":"10.1130/abs/2022pr-376097","title":"DEVELOPING A DIGITAL DATABASE OF KEY FACTORS RESPONSIBLE FOR NATURAL FRACTURE GROWTH IN THE THEBAN NECROPOLIS (LUXOR, EGYPT)","year":2022,"lang":"en","type":"article","venue":"Abstracts with programs - Geological Society of America","topic":"Landslides and related hazards","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada; Government of Canada","keywords":"Key (lock); Natural (archaeology); Computer science; Ancient history; Archaeology; History; Computer security","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003797415,0.0001966718,0.0002937459,0.00001548644,0.0002815936,0.00003391324,0.0005184899,0.00009194036,0.0001991805],"category_scores_gemma":[0.00007769305,0.00009859532,0.0001961117,0.0005604225,0.0008341823,0.0001985497,0.0003014907,0.0005450284,0.000002154281],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001007379,"about_ca_system_score_gemma":0.00006137421,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001684611,"about_ca_topic_score_gemma":0.00001901184,"domain_scores_codex":[0.9982966,0.00006913648,0.0003495378,0.0003322476,0.0005163759,0.0004361129],"domain_scores_gemma":[0.9990236,0.0003617857,0.0003227426,0.0002088389,0.00002391973,0.00005913241],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003025582,0.004832941,0.8321723,0.0003567314,0.0006944163,0.00009166842,0.04510751,0.02107086,0.001622866,0.000910498,0.01729543,0.07281919],"study_design_scores_gemma":[0.003191266,0.005746899,0.7245054,0.000130158,0.0001352154,0.00008031379,0.04862628,0.001899294,0.002369527,0.004171121,0.2079229,0.001221659],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9946983,0.0001023397,0.0004400861,0.003211993,0.0000305343,0.0007333888,0.00004893821,0.00003249516,0.0007019514],"genre_scores_gemma":[0.9856042,0.00003825998,0.01311032,0.0008931981,0.00001211379,0.00007427971,0.0001833753,0.00001197209,0.00007229859],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1906275,"threshold_uncertainty_score":0.4020601,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01668043712700245,"score_gpt":0.2466841921871179,"score_spread":0.2300037550601154,"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."}}