{"id":"W4234085263","doi":"10.1109/jsen.2019.2926014","title":"IEEE Sensors Council Information","year":2019,"lang":"ru","type":"article","venue":"IEEE Sensors Journal","topic":"Diverse Scientific and Economic Studies","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00282186,0.0004579853,0.0009798054,0.0005307134,0.000558826,0.001048154,0.0005122749,0.0003059962,0.02214764],"category_scores_gemma":[0.0002100746,0.0005258108,0.0005231735,0.0003606913,0.0002015481,0.002173865,0.00006937458,0.0007909262,0.2400768],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001469832,"about_ca_system_score_gemma":0.0003070927,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001213178,"about_ca_topic_score_gemma":0.000008060649,"domain_scores_codex":[0.9962851,0.00004916328,0.001840177,0.0005411177,0.0003069023,0.0009774747],"domain_scores_gemma":[0.9967887,0.0001146985,0.001692678,0.0005705078,0.0004733043,0.0003600999],"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":[0.0001408085,0.0001125721,0.008590633,0.0001149802,0.0006570346,0.00003427923,0.008786558,0.02118972,0.00003961911,0.002280829,0.9570541,0.0009988897],"study_design_scores_gemma":[0.002191699,0.0001467141,0.001758939,0.00009193534,0.00005006565,0.0002289002,0.004535554,0.01179617,0.0001256339,0.0006898511,0.9775695,0.0008150931],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6232246,0.0008469985,0.00007259181,0.0004425713,0.046052,0.0002862267,0.0006835919,0.00003338627,0.328358],"genre_scores_gemma":[0.5686978,0.003721934,0.000229348,0.0007089035,0.001427971,0.000003092705,0.000007609748,0.00004850813,0.4251548],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2179292,"threshold_uncertainty_score":0.9999889,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04772874894000192,"score_gpt":0.1999579631817166,"score_spread":0.1522292142417147,"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."}}