{"id":"W6894140512","doi":"10.5281/zenodo.8071646","title":"Meligramma cincta","year":2019,"lang":"es","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Historical Studies in Science","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Cégep de Rivière-du-Loup","funders":"","keywords":"Sequence (biology); Feature (linguistics); Component (thermodynamics)","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":[0.0001606982,0.0008004267,0.0003234698,0.001105744,0.003146709,0.001091987,0.0006558244,0.0006281264,0.02064093],"category_scores_gemma":[0.0004968991,0.0002082521,0.0002073945,0.001049964,0.001252121,0.0009851992,0.001165831,0.0009619073,0.004382251],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001188374,"about_ca_system_score_gemma":0.0003748855,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01496304,"about_ca_topic_score_gemma":0.03836251,"domain_scores_codex":[0.9997417,0.00002562309,0.00002310015,0.0001164714,0.00005583771,0.00003715513],"domain_scores_gemma":[0.9998268,0.00002769331,0.00006295894,0.00002199463,0.0000351356,0.00002536044],"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":[0.0005113051,0.0002150458,0.02879716,0.001306413,0.00009921847,0.009198138,0.009211723,0.0008323051,0.02966705,0.02608804,0.05489932,0.8391743],"study_design_scores_gemma":[0.00002704487,0.0001256002,0.08112585,0.0003593093,0.00005313887,0.005708379,0.001749824,0.0001677304,0.001642665,0.00147428,0.9075386,0.00002753277],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2327541,0.02853455,0.003788306,0.002044022,0.001666183,0.0004619813,0.003304713,0.001062822,0.7263834],"genre_scores_gemma":[0.8947572,0.006017475,0.003298452,0.001525238,0.0005067063,0.000157243,0.001293691,0.00011883,0.09232512],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02064093,"threshold_uncertainty_score":0.06905085,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04167764797047981,"score_gpt":0.2381722343004322,"score_spread":0.1964945863299524,"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."}}