{"id":"W3089371172","doi":"10.1111/1740-9713.01453","title":"When Academia Meets Industry Meets Government","year":2020,"lang":"en","type":"article","venue":"Significance","topic":"Census and Population Estimation","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Government (linguistics); Business; Management; Engineering; Engineering management; Computer science; Economics; Philosophy","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0328084,0.000549459,0.00108323,0.004042122,0.05836518,0.04550014,0.003419986,0.02036417,0.05665747],"category_scores_gemma":[0.08367593,0.001071617,0.000915951,0.007565263,0.02128319,0.02612543,0.02189848,0.02457186,0.01260844],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0464143,"about_ca_system_score_gemma":0.1774984,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3264026,"about_ca_topic_score_gemma":0.4604631,"domain_scores_codex":[0.923772,0.02684847,0.001184568,0.003245868,0.01941,0.02553905],"domain_scores_gemma":[0.8448563,0.02128494,0.004143062,0.004418174,0.03745803,0.08783948],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005603213,0.000155758,0.005469976,0.00008346979,0.00002643723,0.0005029134,0.0337854,0.0001086892,0.0003495785,0.1543197,0.7702326,0.03490949],"study_design_scores_gemma":[0.00001899987,0.00003658596,0.002390226,0.0002160057,0.000009692651,0.000082695,0.1407948,0.00009244334,0.0001982853,0.02402749,0.8320779,0.000054897],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.007340211,0.002032034,0.000626899,0.8567579,0.004995799,0.00003443176,0.00008761789,0.0001199136,0.1280052],"genre_scores_gemma":[0.4533815,0.003538833,0.001134984,0.3403921,0.002874479,0.0001453797,0.0002911524,0.0005425238,0.1976989],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.3264026,"threshold_uncertainty_score":0.6490055,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09169510065264146,"score_gpt":0.3259053651543213,"score_spread":0.2342102645016799,"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."}}