{"id":"W1775295873","doi":"","title":"FISHER (ed.), Archival Information: How to Find It, How to Use it","year":2006,"lang":"en","type":"article","venue":"Archivaria","topic":"Hermeneutics and Narrative Identity","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Information technology; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000146517,0.0001904986,0.0001865006,0.0001842807,0.0004025869,0.001623739,0.0002560495,0.00002354755,0.001088548],"category_scores_gemma":[0.000118386,0.0001720472,0.00008719419,0.00006531288,0.00008330568,0.0009633164,0.0001574168,0.0001559618,0.0008513469],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002789049,"about_ca_system_score_gemma":0.00005036926,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001387844,"about_ca_topic_score_gemma":0.003044012,"domain_scores_codex":[0.998852,0.0000640474,0.0002217865,0.0002043735,0.0002823921,0.0003753749],"domain_scores_gemma":[0.9992256,0.0001272318,0.00006507971,0.0003103626,0.0001013934,0.0001704007],"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":[0.00002207251,0.00003503654,0.0004506029,0.00001070427,0.00001814845,0.000004011277,0.006689441,0.00002594118,0.000182051,0.4170688,0.5743058,0.001187337],"study_design_scores_gemma":[0.0002247711,0.0001056589,0.05121404,0.00002357017,0.00001213895,0.000001816663,0.0002964948,0.0001120252,0.00007783007,0.01093912,0.9367466,0.0002459465],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2405189,0.000003063794,0.001748983,0.07835866,0.001128134,0.0007457324,0.0004500497,0.0001140368,0.6769325],"genre_scores_gemma":[0.9123265,0.000002564402,0.0009120492,0.004779432,0.0007954098,0.00003770372,0.00008976221,0.00001767968,0.08103894],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6718076,"threshold_uncertainty_score":0.9999266,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02905954099429791,"score_gpt":0.2245728928663414,"score_spread":0.1955133518720435,"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."}}