{"id":"W156340125","doi":"","title":"Very close nadiral images: a proposal for quick digging survey","year":2010,"lang":"en","type":"article","venue":"PORTO Publications Open Repository TOrino (Politecnico di Torino)","topic":"3D Surveying and Cultural Heritage","field":"Earth and Planetary Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Orthophoto; Computer science; Total station; Digital elevation model; Metric (unit); Automation; Documentation; Excavation; Photogrammetry; Remote sensing; Artificial intelligence; Geography; Engineering; Cartography; Archaeology","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001907301,0.000403087,0.0004444893,0.0001602731,0.001317723,0.002039043,0.002019825,0.0002425468,0.0004703995],"category_scores_gemma":[0.0004555725,0.0003487704,0.0001942479,0.0006021183,0.0001986889,0.002043022,0.0001613814,0.0005196424,0.0001391499],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004595158,"about_ca_system_score_gemma":0.0008867205,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02957917,"about_ca_topic_score_gemma":0.01604296,"domain_scores_codex":[0.9965072,0.000271683,0.0008027665,0.0009640443,0.0005095315,0.0009447981],"domain_scores_gemma":[0.996556,0.0004571107,0.0003718052,0.001343882,0.0006400298,0.0006311471],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007625573,0.0001315295,0.9796346,0.00003278231,0.00005152233,0.000007100542,0.0001834838,0.000009844326,0.0007787148,0.003904288,0.009057701,0.006132134],"study_design_scores_gemma":[0.0004238299,0.0001285941,0.910724,0.00001583668,0.00002743918,0.00007788483,0.0001313413,0.0001425584,0.0009963509,0.0004005682,0.08640987,0.0005216632],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8918422,0.0004088483,0.0001025321,0.0008135452,0.006663774,0.002469368,0.001319287,0.0005390287,0.09584144],"genre_scores_gemma":[0.9615762,0.00001463296,0.003355645,0.00009642839,0.001166747,0.0001874924,0.001717163,0.00002905016,0.03185664],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07735217,"threshold_uncertainty_score":0.9999824,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0307193394347561,"score_gpt":0.2829430955724949,"score_spread":0.2522237561377388,"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."}}