{"id":"W6944640176","doi":"10.20381/ruor-27862","title":"The Future of Open Data","year":2022,"lang":"en","type":"book","venue":"Open MIND","topic":"E-Government and Public Services","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Open data; Open government; Context (archaeology); Linked data; Geospatial analysis; General partnership; Open science; Government (linguistics)","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":["scholarly_communication","open_science","insufficient_payload"],"consensus_categories":["open_science"],"category_scores_codex":[0.00283195,0.0001053409,0.0002122716,0.00001423425,0.0009182189,0.001391258,0.01860476,0.0001253637,0.06675148],"category_scores_gemma":[0.00003629982,0.00007645147,0.00003267252,0.000110538,0.0002034106,0.000745637,0.01177079,0.0002378475,0.0001476471],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001145079,"about_ca_system_score_gemma":0.002081373,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003884457,"about_ca_topic_score_gemma":0.0717738,"domain_scores_codex":[0.9983538,0.0001878328,0.0002016665,0.0003404716,0.0007350496,0.0001812029],"domain_scores_gemma":[0.9982176,0.0002730133,0.000348783,0.001064684,0.00003901178,0.00005689304],"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":[0.00001816604,0.00001597108,0.00004052886,0.000003972425,0.00005729168,0.000002314202,0.003713682,5.070772e-8,1.898447e-7,0.02783149,0.7536218,0.2146946],"study_design_scores_gemma":[0.00009903788,0.00001497631,0.00001387291,0.00001672876,0.00002946542,1.341435e-7,0.01781755,8.402557e-7,8.423708e-7,0.001831319,0.9800678,0.0001074546],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00003082283,0.001471596,6.075539e-8,0.007951372,0.0008652158,0.0007715785,0.0007003798,6.863687e-7,0.9882083],"genre_scores_gemma":[0.00003418567,0.0008903734,0.0001587061,0.0001489615,0.0008985174,0.00001413553,0.000697719,0.00001218552,0.9971452],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.226446,"threshold_uncertainty_score":0.9996454,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1007263668522834,"score_gpt":0.3863077331592443,"score_spread":0.2855813663069609,"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."}}