{"id":"W6930483264","doi":"10.5281/zenodo.14951399","title":"Coproica digitata","year":2015,"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":"University of Calgary; University of Guelph","funders":"","keywords":"Laminaria digitata; Czech; Identification (biology); Natural (archaeology)","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":[],"consensus_categories":[],"category_scores_codex":[0.00006969336,0.0006302591,0.0002353781,0.00129766,0.00110435,0.0002949085,0.0004231478,0.0003719242,0.01682647],"category_scores_gemma":[0.000373565,0.0002022619,0.0001282869,0.0005823597,0.0003520655,0.0004666754,0.0005749289,0.0002697498,0.003648879],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005018924,"about_ca_system_score_gemma":0.0002038847,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005679734,"about_ca_topic_score_gemma":0.009848377,"domain_scores_codex":[0.9998643,0.00001907694,0.00001071072,0.00006344452,0.00002400386,0.0000184022],"domain_scores_gemma":[0.9998789,0.00002219478,0.00004235303,0.00001601074,0.00002772935,0.00001284072],"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":[0.0006165106,0.0001811391,0.06312599,0.001366931,0.0000825716,0.002774949,0.002397432,0.0006342741,0.07177596,0.00721417,0.02525973,0.8245704],"study_design_scores_gemma":[0.00007760232,0.0003070101,0.3430585,0.0006021046,0.00007616133,0.01069061,0.001150432,0.0003816911,0.005041125,0.0009182137,0.6376592,0.0000374361],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.4145151,0.01697229,0.004308171,0.0004153831,0.0003227054,0.0004026185,0.004205448,0.0007047425,0.5581535],"genre_scores_gemma":[0.9596967,0.002620253,0.002175137,0.0003299795,0.0001117003,0.0001195396,0.001634215,0.00003230401,0.03328023],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01682647,"threshold_uncertainty_score":0.05629021,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07890080335898941,"score_gpt":0.2818252623055107,"score_spread":0.2029244589465213,"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."}}