{"id":"W6893822903","doi":"10.5281/zenodo.6112356","title":"Yoshimotoana Huber, gen. n.","year":2015,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Parasite Biology and Host Interactions","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Dorsum; Margin (machine learning); Sulcus; Vertex (graph theory); Apex (geometry); Cadaver","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":[0.000211144,0.001390959,0.0007273933,0.002011311,0.001545146,0.0003875181,0.00125657,0.0005358048,0.02688014],"category_scores_gemma":[0.000413485,0.0005522778,0.0002084832,0.001626829,0.000624634,0.002217359,0.001119915,0.0006781585,0.01462028],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006197243,"about_ca_system_score_gemma":0.0005504524,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01299975,"about_ca_topic_score_gemma":0.02524358,"domain_scores_codex":[0.9998406,0.00001309925,0.00001907967,0.00008393621,0.00002773773,0.00001543032],"domain_scores_gemma":[0.9997872,0.00002656868,0.00008488569,0.00002065421,0.00005556575,0.00002529381],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0008319051,0.0001227309,0.01602665,0.001497137,0.0001947568,0.002389007,0.002213944,0.0008400357,0.02335461,0.004874649,0.0442735,0.9033812],"study_design_scores_gemma":[0.0004945371,0.0005903534,0.2265727,0.0006910671,0.0005972921,0.008539751,0.004129314,0.001412949,0.004013576,0.004160901,0.748693,0.0001046084],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2759672,0.08249037,0.01669762,0.002119939,0.003031035,0.003158142,0.01302002,0.003964909,0.5995508],"genre_scores_gemma":[0.8452775,0.02066054,0.02022314,0.001507922,0.001063342,0.00126622,0.006850218,0.000253373,0.1028978],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02688014,"threshold_uncertainty_score":0.08992302,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0571192750685203,"score_gpt":0.3048553971510737,"score_spread":0.2477361220825534,"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."}}