{"id":"W7128967791","doi":"10.5281/zenodo.18650609","title":"Megistopoda proxima Seguy 1926","year":2016,"lang":"","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Protist diversity and phylogeny","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Bridge (graph theory); Population; Quarter (Canadian coin); Population decline","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":[0.0001230546,0.001065063,0.0004402043,0.002444594,0.002190248,0.0008955972,0.0006093578,0.0007343835,0.04750944],"category_scores_gemma":[0.0005430125,0.00033645,0.0002373466,0.001930926,0.001000329,0.001604824,0.0009880404,0.000940938,0.01138449],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009384065,"about_ca_system_score_gemma":0.0003360537,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009197352,"about_ca_topic_score_gemma":0.01584183,"domain_scores_codex":[0.9998248,0.00003122147,0.00001477083,0.00005610535,0.00004484894,0.00002833628],"domain_scores_gemma":[0.999909,0.00001873709,0.00002962032,0.00001047831,0.0000233465,0.000008806623],"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":[0.0007227208,0.000103668,0.01059159,0.000855216,0.0000655804,0.00199038,0.00357998,0.0006173104,0.006443346,0.0338052,0.10808,0.8331451],"study_design_scores_gemma":[0.00003133329,0.00005885344,0.02030966,0.0001256534,0.00003143094,0.001551291,0.0005699421,0.00009145091,0.0005581559,0.0014848,0.9751728,0.0000146422],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.04388716,0.01844177,0.003441219,0.0008946429,0.00139997,0.0003396627,0.005610904,0.0005314957,0.9254532],"genre_scores_gemma":[0.6607848,0.01715493,0.007937494,0.001094467,0.001832899,0.0005864345,0.006055634,0.0003815143,0.3041718],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04750944,"threshold_uncertainty_score":0.1589349,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02343641023709553,"score_gpt":0.2231300654846347,"score_spread":0.1996936552475392,"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."}}