{"id":"W4252481587","doi":"10.1515/iupac.79.0935","title":"Biomineralization","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Bone and Dental Protein Studies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; Computer science; Toxicology; Chemistry; Philosophy; Biology; Linguistics","routes":{"ca_aff":true,"ca_fund":false,"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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001883298,0.0003104963,0.0006333789,0.0001845939,0.00008075555,0.00002069951,0.00009542766,0.0002880183,0.00173575],"category_scores_gemma":[0.0003421548,0.0002019618,0.0001602186,0.0001601586,0.0001345583,0.00004917472,0.0001279848,0.00022187,0.000008757387],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002447075,"about_ca_system_score_gemma":0.0003187096,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001345613,"about_ca_topic_score_gemma":0.0001619106,"domain_scores_codex":[0.9981988,0.00002690782,0.0003634687,0.0003524066,0.0007974438,0.0002609554],"domain_scores_gemma":[0.9987354,0.00002647342,0.0001579181,0.0005315064,0.0004206613,0.000128034],"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":[0.0002874181,0.0001846786,0.00002945761,0.0002700467,0.0001595523,0.0001225362,0.000003358283,2.983674e-8,0.00007001057,0.000007459048,0.996429,0.002436501],"study_design_scores_gemma":[0.001646026,0.0003632643,0.000106913,0.0007428486,0.0002661997,0.0000547294,0.00001239033,9.79157e-7,0.00007216254,0.00007651434,0.9964254,0.0002325667],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001238602,0.002194069,0.0001459794,0.001326603,0.0004155558,0.0004307624,0.995136,0.00007202524,0.0001551722],"genre_scores_gemma":[0.00003624056,0.002260139,0.00004543359,0.0008708269,0.001195887,0.00001865809,0.9933646,0.00003118759,0.002177047],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.002203934,"threshold_uncertainty_score":0.9991768,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0193675620957123,"score_gpt":0.4242864229122959,"score_spread":0.4049188608165836,"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."}}