{"id":"W4256574089","doi":"10.1016/s1535-9476(20)32164-2","title":"Calendar","year":2007,"lang":"en","type":"article","venue":"Molecular & Cellular Proteomics","topic":"Mass Spectrometry Techniques and Applications","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002585276,0.0001776688,0.0001494264,0.00007159112,0.00009737279,0.0000223481,0.0003141757,0.0001721483,0.001859566],"category_scores_gemma":[0.00002351352,0.0001920939,0.0001282676,0.0002142607,0.00005647869,0.00003051488,0.00009028743,0.0002889357,0.00006837009],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009783186,"about_ca_system_score_gemma":0.00002938004,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002903107,"about_ca_topic_score_gemma":0.000002639282,"domain_scores_codex":[0.9987758,0.00000695894,0.0002682988,0.0003316011,0.0002244723,0.0003928604],"domain_scores_gemma":[0.9990908,0.00001326843,0.0000904317,0.0006214873,0.00004844478,0.0001355851],"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":[0.000007498992,0.00006168851,0.0001708083,0.00003201782,0.00001413655,0.00007545056,0.00001521006,0.000002750864,0.9749757,0.02287837,0.0001531743,0.001613186],"study_design_scores_gemma":[0.0001527101,0.00001281958,0.00001440523,0.00000996973,0.00001483162,0.00001444968,0.00001710174,0.0000948645,0.9449342,0.00598389,0.04853659,0.0002142021],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6566749,0.0001962662,0.2728492,0.0001830506,0.00002252931,0.000233919,0.00003416252,0.0003284863,0.06947751],"genre_scores_gemma":[0.938893,0.00001239494,0.05917744,0.0001222255,0.0000947287,0.0000639576,0.00005151724,0.00005108233,0.001533667],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2822181,"threshold_uncertainty_score":0.9990529,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006290264478107105,"score_gpt":0.232473212834616,"score_spread":0.2261829483565089,"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."}}