{"id":"W6993061605","doi":"","title":"Newsbrief - measurement device will be boon to window manufacturers and consumers","year":2000,"lang":"en","type":"article","venue":"NPARC","topic":"Diverse Specialized Academic Research","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Window (computing); Service (business); Measure (data warehouse); Measurement device; Data collection","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.002431576,0.0009887556,0.0007712051,0.003406054,0.002125093,0.006556937,0.000831464,0.004358391,0.223344],"category_scores_gemma":[0.02000641,0.0006453866,0.0004149966,0.002850821,0.0008260262,0.004738462,0.001343984,0.003086823,0.1157411],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002056906,"about_ca_system_score_gemma":0.00202557,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01265942,"about_ca_topic_score_gemma":0.01730909,"domain_scores_codex":[0.998061,0.0003307714,0.0001488358,0.0002370999,0.001022139,0.0002001376],"domain_scores_gemma":[0.9836313,0.004912804,0.001502377,0.002441584,0.006237885,0.001274069],"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":[0.0001801134,0.00005672121,0.001613597,0.00009421516,0.000007390468,0.00008138556,0.0001494559,0.00003306118,0.0007387526,0.006590775,0.9372435,0.053211],"study_design_scores_gemma":[0.00003632338,0.00007579286,0.009140229,0.00009959829,0.0000172798,0.00007985466,0.0003078109,0.0002641473,0.001135793,0.0009415511,0.9878714,0.00003016287],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.01816941,0.005299265,0.007279142,0.09367155,0.05492055,0.0006029843,0.04298405,0.007289994,0.7697831],"genre_scores_gemma":[0.02725588,0.00145562,0.001886216,0.005421406,0.005502476,0.0003072795,0.006448476,0.0008140893,0.9509087],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.223344,"threshold_uncertainty_score":0.7471602,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07556168023722372,"score_gpt":0.2588000708127251,"score_spread":0.1832383905755014,"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."}}