{"id":"W6930599037","doi":"10.5281/zenodo.15021152","title":"Euura nigerrima","year":2025,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Tissue Engineering and Regenerative Medicine","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Dorsum; Penis; Margin (machine learning); Arctic; Type (biology)","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":[0.00004292291,0.0003858265,0.0001940629,0.0009717275,0.0008276097,0.0003467381,0.0003651581,0.0004184527,0.03587147],"category_scores_gemma":[0.0001628531,0.0001454652,0.0001233086,0.0005995639,0.0003450798,0.0007878863,0.0007548975,0.0003669644,0.008998851],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000337943,"about_ca_system_score_gemma":0.0001569677,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002929582,"about_ca_topic_score_gemma":0.006443406,"domain_scores_codex":[0.9999363,0.00000931671,0.000007075906,0.0000243577,0.00001194076,0.00001103462],"domain_scores_gemma":[0.9999539,0.000008143684,0.00001538518,0.000006017181,0.00001046437,0.000006069049],"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":[0.000312815,0.00009950266,0.02299295,0.0007791756,0.0000393057,0.002623469,0.001069557,0.0004975413,0.03258594,0.00950817,0.02024795,0.9092436],"study_design_scores_gemma":[0.00007495195,0.0002501688,0.29364,0.001161627,0.0001212031,0.01278912,0.003005425,0.0007165394,0.006519116,0.003933896,0.677736,0.00005196094],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2115427,0.01285358,0.004553606,0.0003949373,0.0004185815,0.0002500547,0.002845632,0.0004648074,0.7666761],"genre_scores_gemma":[0.9233716,0.00463817,0.004082694,0.0006171148,0.00008212432,0.0001131604,0.002738217,0.00005492625,0.06430213],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03587147,"threshold_uncertainty_score":0.120002,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02428098253975178,"score_gpt":0.2690622277910771,"score_spread":0.2447812452513254,"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."}}