{"id":"W6931789274","doi":"10.5281/zenodo.7251758","title":"Swiss National Data and Service Center for the Humanities (DaSCH)","year":2022,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Digital Humanities and Scholarship","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Discovery Air (Canada)","funders":"","keywords":"Interoperability; Service (business); Identifier; Presentation (obstetrics); Object (grammar); Data management plan; Data management; Metadata","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006875239,0.001395037,0.001047873,0.008560212,0.001944569,0.007059522,0.001819773,0.002028301,0.2050817],"category_scores_gemma":[0.02203433,0.0006179214,0.0006061107,0.01310844,0.001239333,0.004933248,0.008940672,0.00189392,0.1066478],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003859098,"about_ca_system_score_gemma":0.01261809,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02863982,"about_ca_topic_score_gemma":0.01381687,"domain_scores_codex":[0.9921728,0.001762125,0.0007531431,0.0009668169,0.003366487,0.0009784952],"domain_scores_gemma":[0.9848327,0.002896519,0.001155062,0.004902176,0.003991584,0.002221852],"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":[0.0003104259,0.00003169915,0.003138236,0.0008038362,0.00003175543,0.0002039709,0.0005731392,0.0005817203,0.001293408,0.05459807,0.8435745,0.0948593],"study_design_scores_gemma":[0.00004747067,0.00001535748,0.003530304,0.0002060471,0.00000865462,0.00009329259,0.0002104812,0.0005729204,0.0007262122,0.004399964,0.9901441,0.00004515824],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.007980433,0.003603301,0.02706686,0.01329047,0.002041651,0.0007111831,0.7069437,0.02486393,0.2134984],"genre_scores_gemma":[0.06456763,0.003353884,0.0234544,0.001283621,0.0006795509,0.002425666,0.8188328,0.005930578,0.07947184],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.2050817,"threshold_uncertainty_score":0.6860665,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1761894071101007,"score_gpt":0.2635578407235102,"score_spread":0.08736843361340951,"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."}}