{"id":"W6911830049","doi":"10.5281/zenodo.14597178","title":"Krateriske Huber 2015","year":2024,"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":"Natural Resources Canada","funders":"","keywords":"Sulcus; Genus; Margin (machine learning); Face (sociological concept); Dorsum","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":[0.0003387274,0.0007854264,0.0004654684,0.002091693,0.001033555,0.001358603,0.0008366274,0.0008114779,0.1010894],"category_scores_gemma":[0.0007285043,0.0003571267,0.0002754403,0.001142018,0.0006283713,0.001796604,0.001904926,0.001020801,0.04421095],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00077913,"about_ca_system_score_gemma":0.0006228081,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005448719,"about_ca_topic_score_gemma":0.007659367,"domain_scores_codex":[0.9996383,0.00004128859,0.0000410619,0.0001283937,0.00009342227,0.00005746924],"domain_scores_gemma":[0.999804,0.00003005737,0.00005730592,0.00005345831,0.00003352889,0.00002173827],"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":[0.0002627979,0.00007922723,0.002737645,0.0008618571,0.00005092753,0.001567912,0.0009831458,0.0008191777,0.007607254,0.0242885,0.1128492,0.8478923],"study_design_scores_gemma":[0.00001878179,0.00003889889,0.006641556,0.0002370853,0.00002007244,0.00208623,0.0001909091,0.000223248,0.001723574,0.00227541,0.9865267,0.00001761819],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.05379486,0.07284723,0.0188452,0.003368924,0.004976465,0.0005511235,0.01680236,0.005293695,0.8235201],"genre_scores_gemma":[0.3924826,0.03180504,0.02993175,0.0009806033,0.001361434,0.000306397,0.01092932,0.001640472,0.5305623],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1010894,"threshold_uncertainty_score":0.3381779,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02747537851379461,"score_gpt":0.311236420535504,"score_spread":0.2837610420217094,"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."}}