{"id":"W2593709101","doi":"","title":"3D acquisition of Donatello’s Maddalena: protocols, good practices and benchmarking","year":2003,"lang":"en","type":"article","venue":"NPARC","topic":"3D Surveying and Cultural Heritage","field":"Earth and Planetary Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Università degli Studi di Firenze","keywords":"Benchmarking; Computer science; Business","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004586247,0.00007493223,0.0001037821,0.0000212192,0.00009518692,0.00003897082,0.00006013143,0.00004618042,0.002608772],"category_scores_gemma":[0.000064574,0.0000561777,0.00001938343,0.00009569239,0.0000453859,0.0002341389,0.000003776801,0.00007572539,0.0000225019],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000001450058,"about_ca_system_score_gemma":0.00001881916,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001455768,"about_ca_topic_score_gemma":0.0002698627,"domain_scores_codex":[0.9992715,0.0001429033,0.0001316437,0.0001529779,0.0001549841,0.0001459625],"domain_scores_gemma":[0.9995735,0.00009910065,0.0001558958,0.00008636819,0.00003078118,0.00005440807],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005031505,0.00003417893,0.8880177,0.0001317978,0.00001870263,0.00001187125,0.0003923911,0.00003275648,0.00465031,0.0006365862,0.0003898429,0.1056336],"study_design_scores_gemma":[0.0006995695,0.0005734559,0.9351212,0.0001643075,0.0000260701,0.0000848089,0.0006240595,0.00140004,0.005435509,0.004414931,0.05108259,0.0003734462],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7981488,0.0002485592,0.00002077242,0.00008517947,0.00009057989,0.001316142,0.00002648139,0.00002651457,0.200037],"genre_scores_gemma":[0.9954612,0.00003420721,0.004077721,0.00004518436,0.00003303361,0.00002412996,0.00002170084,0.000001710785,0.0003011449],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1997358,"threshold_uncertainty_score":0.998303,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03122369336310637,"score_gpt":0.2597988714009999,"score_spread":0.2285751780378936,"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."}}