{"id":"W4288060410","doi":"10.18357/kula.169","title":"The Power to Structure","year":2022,"lang":"en","type":"article","venue":"KULA knowledge creation dissemination and preservation studies","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Social Sciences and Humanities Research Council of Canada; Canada Research Chairs","keywords":"Metadata; World Wide Web; Computer science; Interoperability; Context (archaeology); Meaning (existential); Ontology; Data science; Situated; Data sharing; Knowledge management; Epistemology; Geography; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0004379447,0.000100329,0.000109389,0.0001017026,0.001406407,0.0001815171,0.000378818,0.00001948867,0.0000266119],"category_scores_gemma":[0.0007160897,0.00007272085,0.00002398746,0.0005165534,0.00004905309,0.0002870126,0.0005875684,0.00007871918,0.000005970939],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005569039,"about_ca_system_score_gemma":0.00002271426,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003197916,"about_ca_topic_score_gemma":0.00004566219,"domain_scores_codex":[0.9990341,0.000142518,0.0001969688,0.0002450763,0.000244333,0.0001369958],"domain_scores_gemma":[0.9985842,0.0006973827,0.00008018018,0.0002757499,0.0003242263,0.00003828929],"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":[0.00003463594,0.00007234284,0.00976282,0.00003120322,0.0001066554,0.000001283178,0.1193274,0.0001681771,0.001326679,0.6095524,0.1424635,0.1171529],"study_design_scores_gemma":[0.0002444778,0.0001087649,0.164327,0.00001890337,0.00001384709,0.000008202927,0.01124998,0.006564369,0.001161779,0.01828374,0.7977766,0.0002423389],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6575501,0.03803972,0.08535407,0.1136164,0.004331063,0.002295512,0.00003774261,0.0009889529,0.09778649],"genre_scores_gemma":[0.9713674,0.0001350492,0.0009868512,0.0002199174,0.00003222166,0.0001593333,0.000009751931,0.000005217036,0.02708427],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.655313,"threshold_uncertainty_score":0.9998936,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02864515189273641,"score_gpt":0.3502146982249096,"score_spread":0.3215695463321732,"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."}}