{"id":"W1494683608","doi":"","title":"Government research directory 2001 : a descriptive guide to more than 4,800 U.S. and Canadian government research and development centers, institutes, laboratories, bureaus, test facilities, experiment stations, data collection and analysis centers, and grants management and research coordinating offices in agriculture, commerce, education, energy, engineering, environment, the humanities, medicine, military science, and basic and applied sceicnes","year":2001,"lang":"en","type":"article","venue":"Medical Entomology and Zoology","topic":"Research, Science, and Academia","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Government (linguistics); Data collection; Directory; Test (biology); Descriptive statistics; Library science; Descriptive research; Business; Public administration; Engineering; Political science; Computer science; Sociology; Social science; Statistics","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":["sts"],"consensus_categories":["sts"],"category_scores_codex":[0.0161999,0.0002521183,0.0004332171,0.001212798,0.002247789,0.0002947355,0.0006219433,0.0001687737,0.00004242599],"category_scores_gemma":[0.002935913,0.0001760398,0.000006489991,0.002131602,0.008271134,0.0004074691,0.00182565,0.0006502346,4.790156e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006218764,"about_ca_system_score_gemma":0.0006537016,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.07692216,"about_ca_topic_score_gemma":0.1322099,"domain_scores_codex":[0.9931364,0.0007462111,0.0005960015,0.001358958,0.003166447,0.0009959486],"domain_scores_gemma":[0.9961389,0.00223118,0.00007056241,0.0003974721,0.0002909366,0.000870973],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00020892,0.0002661226,0.8864309,0.000103613,0.0001563399,0.00008624932,0.02140177,0.000002550498,0.0003655511,0.01205429,0.02080161,0.05812214],"study_design_scores_gemma":[0.001017086,0.0003343225,0.7167307,0.0001071415,0.00002690997,0.0001048318,0.08137662,0.0008228348,0.00005119475,0.0007224448,0.1984594,0.0002465337],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9741786,0.017717,0.0001562271,0.005304896,0.0001047296,0.000925192,0.0001382673,0.000009668277,0.001465395],"genre_scores_gemma":[0.9702831,0.02545346,0.000802218,0.0004334163,0.0000515294,0.000263173,0.00005531734,0.00001055649,0.002647253],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1776578,"threshold_uncertainty_score":0.9990512,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1145416855280147,"score_gpt":0.39303057207943,"score_spread":0.2784888865514153,"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."}}