{"id":"W4327936214","doi":"10.1080/20964471.2023.2187659","title":"Publishing Eurac Research data on the GEOSS Platform","year":2023,"lang":"en","type":"article","venue":"Big Earth Data","topic":"Scientific Computing and Data Management","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Horizon 2020 Framework Programme; Università degli Studi della Basilicata; Università degli Studi di Firenze; European Geosciences Union; European Commission; European Space Agency; Newlife the Charity for Disabled Children; Innovation, Science and Economic Development Canada; National Science Foundation","keywords":"Computer science; Data publishing; Publishing; Process (computing); Data science; World Wide Web","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.009404381,0.0006636119,0.0008594093,0.01054679,0.001189193,0.006649026,0.001507638,0.0008334253,0.02234243],"category_scores_gemma":[0.02892322,0.0004682654,0.0007664962,0.02014883,0.0007761524,0.005325781,0.004550678,0.0017159,0.01563026],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001625802,"about_ca_system_score_gemma":0.006765828,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007286259,"about_ca_topic_score_gemma":0.006003457,"domain_scores_codex":[0.9910501,0.00158154,0.001180038,0.001017527,0.004698179,0.0004726808],"domain_scores_gemma":[0.9651953,0.006501747,0.002424591,0.01571775,0.008732811,0.001427828],"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":[0.0005364628,0.00009294735,0.01541195,0.0009196035,0.0001575093,0.0004983682,0.001599418,0.00290423,0.008344658,0.08601475,0.7220623,0.1614578],"study_design_scores_gemma":[0.00002621743,0.00001659924,0.005825531,0.0001209683,0.0000141946,0.00009644434,0.0004514775,0.00105665,0.003462615,0.01001278,0.9788768,0.00003963023],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.03846515,0.002500787,0.07755791,0.007710294,0.004525651,0.0009828093,0.6947752,0.02265247,0.1508298],"genre_scores_gemma":[0.09005719,0.00311981,0.08536705,0.0009425353,0.001436811,0.0008308165,0.7688999,0.008204347,0.04114162],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.993351,"threshold_uncertainty_score":0.07474291,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.9209924926776032,"score_gpt":0.5550802865390005,"score_spread":0.3659122061386026,"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."}}