{"id":"W3097706132","doi":"10.47315/archives2018.313-314.007","title":"The Methodology of Archival Science and Archival Method: the Discussion Continues","year":2018,"lang":"en","type":"article","venue":"Archivi Ukraїni","topic":"Digital and Traditional Archives Management","field":"Arts and Humanities","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Archival science; Computer science; Data science; Library science","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":["sts"],"consensus_categories":["sts"],"category_scores_codex":[0.001549325,0.0001336872,0.0001627436,0.0001018672,0.001438324,0.0002420251,0.0006252103,0.000003290497,0.00001752155],"category_scores_gemma":[0.0002479585,0.00005280503,0.00007160612,0.00006705771,0.009106524,0.0001901669,0.0005037371,0.0001370595,0.00002002923],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005732864,"about_ca_system_score_gemma":0.00005383591,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009261058,"about_ca_topic_score_gemma":0.0001102926,"domain_scores_codex":[0.9984286,0.0003024462,0.0002511867,0.0002753276,0.0004011269,0.0003412434],"domain_scores_gemma":[0.9976399,0.00178168,0.0001129781,0.0003103527,0.00007916224,0.00007591426],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00004897754,0.00002428625,0.00001463441,0.000008112098,0.00002615209,6.592355e-7,0.01193334,4.061419e-7,0.0004253844,0.6955346,0.0009197352,0.2910637],"study_design_scores_gemma":[0.0001310284,0.0002448424,0.03231861,0.00002512538,0.00002388057,0.000008185134,0.0009364686,0.0002997113,0.0004963125,0.617426,0.347988,0.0001018294],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.06944218,0.00002598732,0.00304961,0.009815496,0.0005951374,0.0003351624,0.00006380359,0.0000415969,0.916631],"genre_scores_gemma":[0.9882273,0.00003135239,0.004763224,0.0004712348,0.0005473,0.00002328362,0.000005197217,0.00001186227,0.005919209],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9187852,"threshold_uncertainty_score":0.9998617,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07342905071459022,"score_gpt":0.2983268096650843,"score_spread":0.2248977589504941,"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."}}