{"id":"W6894226315","doi":"10.5281/zenodo.6913361","title":"The European Open Science Cloud (EOSC) and Its Implications for the Digital Humanities and Social Sciences","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":"Canarie","funders":"Horizon 2020 Framework Programme","keywords":"Cloud computing; European commission; Digital humanities; Open science; Open data; European Research Area; Sustainability; Digital preservation; Citizen science","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":"codex-gemma-dda1882f352a","candidate_categories":["sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.002159383,0.00009506256,0.00007399345,0.00008318787,0.05886983,0.02221131,0.002416831,0.000006422648,0.0008700991],"category_scores_gemma":[0.0002436555,0.00006761809,0.0000271208,0.0001290735,0.002263715,0.001024141,0.004651216,0.0001627179,0.0000811365],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005074489,"about_ca_system_score_gemma":0.000009943934,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001080686,"about_ca_topic_score_gemma":0.000004466826,"domain_scores_codex":[0.9988036,0.0001554285,0.0001615166,0.0003002295,0.0002723013,0.0003069742],"domain_scores_gemma":[0.9992589,0.0001321618,0.00008564504,0.0001812804,0.0003052513,0.00003681114],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001485138,0.00002483793,0.000001366934,0.000008170686,0.00001101713,3.237019e-7,0.0109483,0.000001157991,0.00003110089,0.9012051,0.0427409,0.04501287],"study_design_scores_gemma":[0.0001708024,0.0001904207,0.0004928486,0.000003058792,0.000007789341,0.0000220606,0.01818334,0.00004346911,0.000002593106,0.004843557,0.9759374,0.0001026144],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.03747239,0.0003933829,0.00002009068,0.005995007,0.0002077043,0.0008727846,0.001135145,0.0001922726,0.9537112],"genre_scores_gemma":[0.990407,0.00003191362,0.000003087648,0.0004272879,0.0002831206,6.870474e-7,0.0001071193,0.0002121266,0.008527642],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9529346,"threshold_uncertainty_score":0.9788038,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1629068491634925,"score_gpt":0.2865037734648308,"score_spread":0.1235969243013383,"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."}}