{"id":"W7071166923","doi":"","title":"Russkaja astrologičeskaja knižnostʹ XI-pervaja četvertʹ XVIII veka = Astrology in Russia : (11th-first quarter of 18th centuries)","year":2019,"lang":"en","type":"article","venue":"","topic":"QR Code Applications and Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Astrology; Quarter (Canadian coin); Government (linguistics); Period (music)","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":[0.0002600583,0.0002762789,0.0004676064,0.0003654393,0.00008054991,0.0000673133,0.001879226,0.0002721201,0.0002688223],"category_scores_gemma":[0.00002865197,0.0002257485,0.000118409,0.000782014,0.0001949481,0.0004327314,0.0006147467,0.0003365617,0.0004704254],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006008281,"about_ca_system_score_gemma":0.00008177076,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002365504,"about_ca_topic_score_gemma":0.0002948952,"domain_scores_codex":[0.9977805,0.00005758719,0.0005485474,0.0007246326,0.0002684449,0.0006202999],"domain_scores_gemma":[0.9979103,0.0001455292,0.0001934375,0.001601134,0.00007805208,0.00007160359],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00005067296,0.0004514475,0.2270974,0.00004263909,0.00005535709,0.00001144668,0.0006705496,0.0002840032,0.001896296,0.7484873,0.002019249,0.01893367],"study_design_scores_gemma":[0.003766476,0.002143962,0.8789216,0.00007721483,0.00002676594,0.00005701945,0.001075847,0.02496083,0.007810178,0.01599214,0.06403325,0.001134708],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9037306,0.0002536421,0.05954527,0.01060182,0.0003971612,0.0008575204,0.00001256884,0.0007795796,0.02382187],"genre_scores_gemma":[0.9731797,0.00003852995,0.02604923,0.0002969614,0.00001849517,0.00007785563,0.000005713579,0.00001345856,0.0003200335],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7324951,"threshold_uncertainty_score":0.9205758,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006424321492805586,"score_gpt":0.2059595910942369,"score_spread":0.1995352696014313,"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."}}