{"id":"W6942271635","doi":"10.14288/1.0421948","title":"A comparison of minimally-invasive sampling techniques for ZooMS analysis of bone artifacts: MALDI-TOF mass spectra","year":2022,"lang":"en","type":"dataset","venue":"Open Collections","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Antler; Artifact (error); Sampling (signal processing); Calibration; Polishing; Reliability (semiconductor); High resolution; Resolution (logic)","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":[],"consensus_categories":[],"category_scores_codex":[0.001318973,0.0008102762,0.0003590872,0.00110387,0.0003259056,0.0007249539,0.0007235808,0.0008921377,0.00170405],"category_scores_gemma":[0.001715968,0.0003544953,0.0004311278,0.0006672649,0.0004781272,0.0009486836,0.0006195144,0.0006817933,0.0008745731],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002320397,"about_ca_system_score_gemma":0.0003358036,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005695052,"about_ca_topic_score_gemma":0.001473062,"domain_scores_codex":[0.9989349,0.0001196275,0.00005875303,0.0002103068,0.000619686,0.00005670698],"domain_scores_gemma":[0.9991257,0.0003240521,0.0001422889,0.00007690382,0.0002784652,0.00005260519],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001623183,0.00003780679,0.0005082497,0.000177782,0.00002781097,0.00007165505,0.00005426756,0.0001081349,0.9775814,0.0001236469,0.0003120305,0.0208348],"study_design_scores_gemma":[0.00002832255,0.0007857172,0.01467822,0.00004726113,0.00009483526,0.001425122,0.0001939294,0.005864291,0.9662737,0.0001756778,0.01031788,0.0001149666],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"dataset","genre_scores_codex":[0.6551077,0.01743739,0.3159348,0.0007178894,0.0006104489,0.0004962827,0.001451968,0.00183202,0.006411434],"genre_scores_gemma":[0.4933904,0.01224141,0.4842471,0.0006980379,0.000160608,0.0004614836,0.001601213,0.0003974817,0.00680225],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.00170405,"threshold_uncertainty_score":0.006975472,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07400870026551608,"score_gpt":0.3808212375352941,"score_spread":0.306812537269778,"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."}}