{"id":"W4384302929","doi":"10.2172/1989385","title":"Pacific Northwest National Laboratory Regional Populations – 2020 Census: Richland Campus and Sequim Campus","year":2023,"lang":"en","type":"report","venue":"","topic":"Survey Methodology and Nonresponse","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Pacific Northwest National Laboratory; Battelle","keywords":"Census; Geography; National laboratory; University campus; Archaeology; Demography; Library science; Engineering; Population; Sociology; Computer science; Engineering physics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[{"model":"gpt","categories":[],"domain":null,"study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"},{"model":"opus","categories":[],"domain":null,"study_design":"observational","genre":"other","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"}],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001456335,0.001093312,0.0004366052,0.002940659,0.0009401396,0.001131902,0.001507676,0.0005480426,0.02050066],"category_scores_gemma":[0.003838758,0.0006212188,0.0004357529,0.005614648,0.0002043422,0.00115105,0.0008951699,0.001331023,0.01793392],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005145454,"about_ca_system_score_gemma":0.01353113,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.5848818,"about_ca_topic_score_gemma":0.556244,"domain_scores_codex":[0.9990576,0.00008960097,0.00007433504,0.0001016063,0.0005477864,0.0001291658],"domain_scores_gemma":[0.996437,0.0001849536,0.0002261796,0.0001206979,0.002782022,0.0002492322],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.00003396462,0.00007707525,0.009667089,0.0001487685,0.00001558535,0.00002395222,0.00007722983,0.0002047579,0.00007932411,0.0006457668,0.9771152,0.01191132],"study_design_scores_gemma":[0.0001018155,0.00004927173,0.1876077,0.0004171027,0.00002918688,0.00008066007,0.0006884161,0.0009499128,0.000761267,0.0003213769,0.8089489,0.0000443168],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.005061335,0.0002574043,0.0006271412,0.0006178615,0.0002173326,0.0009760878,0.9500899,0.0002588174,0.04189416],"genre_scores_gemma":[0.01579436,0.001554706,0.005561276,0.001033119,0.00009310666,0.004551404,0.9174287,0.0002061413,0.05377727],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5848818,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3725251293687136,"score_gpt":0.4834254786677233,"score_spread":0.1109003492990097,"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."}}