{"id":"W1582249215","doi":"","title":"Messages from MARS: Machine-Assisted Reference Section","year":2002,"lang":"en","type":"article","venue":"Reference & User Services Quarterly","topic":"Library Collection Development and Digital Resources","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Mars Exploration Program; Library science; Martian; Exploration of Mars; Section (typography); Presentation (obstetrics); World Wide Web; Computer science; Engineering; Medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001029314,0.0003645275,0.0003066439,0.0002572926,0.0002942947,0.001421534,0.001330202,0.0002066793,0.0008147326],"category_scores_gemma":[0.000004290601,0.0003197154,0.00007659157,0.0009594377,0.0000325144,0.004216803,0.0001632706,0.0003127054,0.0008792935],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005795236,"about_ca_system_score_gemma":0.0000367505,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000558965,"about_ca_topic_score_gemma":0.0004961667,"domain_scores_codex":[0.9974809,0.0001368615,0.0004687259,0.0008534216,0.0005918268,0.0004682758],"domain_scores_gemma":[0.9984602,0.0001342108,0.000221001,0.0008434741,0.0001153835,0.0002257627],"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":[0.0001202176,0.0007920031,0.03686649,0.0002184638,0.0003152844,0.0001479125,0.01695953,0.00001638583,0.001524323,0.02039688,0.009553949,0.9130886],"study_design_scores_gemma":[0.002264122,0.001289761,0.3763216,0.0003576026,0.00004786202,0.00007243481,0.001182673,0.02537944,0.002027802,0.01406232,0.57478,0.002214317],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.816477,0.001239018,0.009370681,0.001098644,0.001040205,0.0003943661,0.0000554996,0.001764445,0.1685601],"genre_scores_gemma":[0.9867361,0.00009922234,0.003610603,0.0007208642,0.0001275213,0.00004099713,0.00007394662,0.00002224499,0.008568561],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9108742,"threshold_uncertainty_score":0.9999255,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02525802483441244,"score_gpt":0.212074236070555,"score_spread":0.1868162112361425,"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."}}