{"id":"W2772469707","doi":"10.4018/ijcini.2017100103","title":"NBPMF","year":2017,"lang":"en","type":"article","venue":"International Journal of Cognitive Informatics and Natural Intelligence","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Computer science; Matching (statistics); Inference; Function (biology); Filter (signal processing); Bipartite graph; Probability mass function; Mass spectrometry; Data mining; Algorithm; Artificial intelligence; Probability density function; Statistics; Chromatography; Theoretical computer science; Mathematics; Chemistry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00123413,0.001488791,0.001009847,0.002104328,0.0009498178,0.001083383,0.002777011,0.001429975,0.02108148],"category_scores_gemma":[0.005919464,0.0006129087,0.001478928,0.001219601,0.0003207123,0.002071829,0.001273735,0.001386311,0.00769347],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008254448,"about_ca_system_score_gemma":0.001225021,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008964638,"about_ca_topic_score_gemma":0.007390894,"domain_scores_codex":[0.999339,0.00008084222,0.0000399079,0.0002007273,0.000277228,0.00006221841],"domain_scores_gemma":[0.9990952,0.0003537304,0.0000661727,0.0001857525,0.0002598062,0.00003938903],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005606555,0.0001751579,0.004881585,0.0006488566,0.0002547317,0.0003469995,0.0001378791,0.08139324,0.007956424,0.01479502,0.1158089,0.7730405],"study_design_scores_gemma":[0.00006455633,0.00004175892,0.000982897,0.00004999958,0.00004481207,0.000323575,0.00003140331,0.918888,0.009222348,0.01464631,0.05566985,0.00003449209],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.006011151,0.0004944609,0.9199843,0.0002461587,0.0002475033,0.0001842947,0.006142552,0.06060682,0.006082832],"genre_scores_gemma":[0.1014683,0.0006942943,0.8574067,0.0002966843,0.0001377046,0.0006054559,0.02250453,0.005066006,0.0118203],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.9789185,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01954277042598941,"score_gpt":0.3476818837583908,"score_spread":0.3281391133324014,"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."}}