{"id":"W6930607267","doi":"10.5281/zenodo.14597177","title":"Krateriske Huber 2015","year":2024,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Survey Methodology and Nonresponse","field":"Social Sciences","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":[0.000364477,0.0007101441,0.0004113829,0.002062113,0.001011007,0.00124683,0.0008039886,0.0007205894,0.0913181],"category_scores_gemma":[0.0008184037,0.0003204803,0.0002497882,0.001186831,0.0005618309,0.00163166,0.001718518,0.0009033521,0.03467951],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000788,"about_ca_system_score_gemma":0.0006366136,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006222442,"about_ca_topic_score_gemma":0.008781819,"domain_scores_codex":[0.9996411,0.00004263902,0.00004043207,0.0001251869,0.00009327644,0.00005737641],"domain_scores_gemma":[0.9997863,0.00003610455,0.00006096958,0.00005794104,0.00003697946,0.00002167784],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002536926,0.00007956304,0.003218704,0.0008077141,0.00004721108,0.001343941,0.001104062,0.0006850099,0.006230484,0.02487716,0.112231,0.8491215],"study_design_scores_gemma":[0.00001793797,0.00004029389,0.008318095,0.0002380597,0.00001943878,0.001775342,0.0002321227,0.0001989406,0.001569829,0.002282615,0.9852909,0.00001647026],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.06182856,0.07055212,0.01906208,0.003644304,0.004392233,0.0006265898,0.01747673,0.004615152,0.8178023],"genre_scores_gemma":[0.4159798,0.02989122,0.02767235,0.001019812,0.00115019,0.0003412262,0.009757617,0.001289532,0.5128982],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.0913181,"threshold_uncertainty_score":0.3054895,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2048855883454948,"score_gpt":0.4147326603172115,"score_spread":0.2098470719717167,"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."}}