{"id":"W6968483934","doi":"10.5281/zenodo.15363243","title":"The Open Science approach of the Intergovernmental Panel on Climate Change (IPCC)","year":2025,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Research Data Management Practices","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ouranos","funders":"","keywords":"Framing (construction); Climate change; Downscaling; Documentation; Transparency (behavior); Open science; Open data; 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":[{"model":"gemma","categories":["open_science"],"domain":null,"study_design":"not_applicable","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"medium","status":"direct model label, unvalidated"},{"model":"gpt","categories":["open_science"],"domain":null,"study_design":"not_applicable","genre":"commentary","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"}],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.1009381,0.00185602,0.001629095,0.01056438,0.006071563,0.02526397,0.006299859,0.01387892,0.01094267],"category_scores_gemma":[0.09652708,0.001283518,0.003207421,0.01535561,0.02190015,0.02466651,0.0202254,0.0215516,0.005418593],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01435116,"about_ca_system_score_gemma":0.04769319,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01873136,"about_ca_topic_score_gemma":0.00904424,"domain_scores_codex":[0.8661867,0.06316658,0.008267894,0.01057922,0.04844107,0.003358559],"domain_scores_gemma":[0.8628386,0.05912352,0.007099547,0.03744914,0.02950304,0.00398606],"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":[0.00002242782,0.00003974214,0.0002369703,0.0005694141,0.00004596595,0.00004407528,0.00205765,0.001130769,0.0002843451,0.8926767,0.05699052,0.04590148],"study_design_scores_gemma":[0.00001381001,0.00002074004,0.0003495232,0.0007355111,0.00002548362,0.00005905144,0.0005096601,0.0005514306,0.0003673968,0.3601231,0.6371949,0.00004948088],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.002281811,0.01012028,0.5401512,0.1519882,0.01335923,0.002172366,0.005186507,0.002160797,0.2725796],"genre_scores_gemma":[0.09172852,0.0228069,0.7255083,0.04743576,0.007634388,0.01090525,0.009729283,0.003111595,0.08113994],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.9937001,"threshold_uncertainty_score":0.5338179,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1475460022824101,"score_gpt":0.3269886946217394,"score_spread":0.1794426923393293,"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."}}