{"id":"W4323311571","doi":"10.1002/mgr.32125","title":"Call In Fresh Recruits During Your Last Quarter","year":2023,"lang":"en","type":"article","venue":"˜The œmajor gifts report","topic":"Sociopolitical Dynamics in Russia","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Quarter (Canadian coin); Citation; Bit (key); Advertising; Library science; Computer science; History; Business; Computer security","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":[],"consensus_categories":[],"category_scores_codex":[0.001688148,0.0001477849,0.0002183087,0.0001230462,0.0005318362,0.0001023334,0.00044409,0.0001951239,0.000176935],"category_scores_gemma":[0.000547621,0.0001232614,0.0001161531,0.0008596969,0.0004211783,0.0001430952,0.0001326924,0.0003805359,0.0005429317],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003078422,"about_ca_system_score_gemma":0.0002330803,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005515049,"about_ca_topic_score_gemma":0.03268475,"domain_scores_codex":[0.9973664,0.0002199613,0.0004963401,0.0003985763,0.0007184403,0.0008002685],"domain_scores_gemma":[0.9988241,0.0002745402,0.0001347367,0.0005046802,0.00007446627,0.0001874538],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004343368,0.0002742315,0.7206435,0.0001078555,0.0001657709,0.01152636,0.0874434,0.00009029011,0.001075195,0.1405093,0.03669861,0.001422071],"study_design_scores_gemma":[0.00059729,0.00002895023,0.8851058,0.0000969807,0.00003421037,0.0001100462,0.0213104,0.0003198296,0.00005233644,0.04308609,0.04867993,0.0005781749],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8790224,0.0000245217,0.00001400637,0.003774537,0.0009636694,0.0003632856,0.000007478378,0.0003049042,0.1155253],"genre_scores_gemma":[0.9760665,0.00001563021,0.00005246635,0.0001846264,0.0004853914,0.00007791266,0.0000107922,0.00002834659,0.02307828],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1644623,"threshold_uncertainty_score":0.9849662,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03878304047779377,"score_gpt":0.3457718169568721,"score_spread":0.3069887764790783,"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."}}