{"id":"W6950160120","doi":"10.5281/zenodo.6061030","title":"Hemeromyia washingtona","year":2016,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Prenatal Screening and Diagnostics","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Holotype; Identification (biology); Malaise; Selection (genetic algorithm)","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":[0.00009928168,0.0002996455,0.0001584105,0.001036641,0.001536228,0.0002542087,0.0003328527,0.0003311283,0.006111455],"category_scores_gemma":[0.0003797607,0.0001432163,0.00008283574,0.0005847563,0.0003897239,0.0003596408,0.0004548073,0.0003180805,0.001075436],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001216685,"about_ca_system_score_gemma":0.0009009676,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1318234,"about_ca_topic_score_gemma":0.3056827,"domain_scores_codex":[0.9998953,0.000008220471,0.000006003045,0.00003969244,0.00002856272,0.00002212456],"domain_scores_gemma":[0.9998856,0.00001682698,0.00002424876,0.00001293441,0.00004168051,0.00001878976],"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":[0.0007019767,0.00009944849,0.09235112,0.0008136489,0.00005372079,0.004002437,0.004792374,0.0007014818,0.1413654,0.005095829,0.02970815,0.7203144],"study_design_scores_gemma":[0.00006636552,0.0002189683,0.680196,0.0008730112,0.00007334771,0.006044399,0.003256978,0.0004055593,0.006289776,0.00134614,0.301178,0.00005141415],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.6863706,0.007514117,0.002652741,0.0006269959,0.0003132511,0.0002177419,0.003194889,0.0002808725,0.2988288],"genre_scores_gemma":[0.9699197,0.002003761,0.002434322,0.0003456007,0.00004658485,0.00005292173,0.001089224,0.00002163046,0.02408624],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1318234,"threshold_uncertainty_score":0.2621122,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03624162072520056,"score_gpt":0.2577537735847913,"score_spread":0.2215121528595908,"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."}}