{"id":"W3159983384","doi":"10.29024/joa.41","title":"Urban Planning Academics and Twitter: Who and what?","year":2021,"lang":"en","type":"article","venue":"Journal of Altmetrics","topic":"Social Media and Politics","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Scholarship; Social media; Public relations; Urban planning; Sociology; Resource (disambiguation); Political science; Computer science; World Wide Web; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.002404376,0.0001796311,0.0003292802,0.002398887,0.002865785,0.007476022,0.0005024167,0.0007604774,0.007664264],"category_scores_gemma":[0.01009307,0.0002025583,0.0001920842,0.01128254,0.002530349,0.006111544,0.002351467,0.001151537,0.001346055],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003696665,"about_ca_system_score_gemma":0.004317145,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04097606,"about_ca_topic_score_gemma":0.07694541,"domain_scores_codex":[0.9980021,0.0009183452,0.00009626768,0.0001659759,0.0004613222,0.0003559879],"domain_scores_gemma":[0.994049,0.002680721,0.001261248,0.0002329951,0.000782673,0.0009934702],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001228467,0.0001142879,0.4833081,0.0007239847,0.00007255229,0.00084003,0.1225464,0.0005569012,0.0003106224,0.04685593,0.0749085,0.2696398],"study_design_scores_gemma":[0.000009216116,0.0000513106,0.2023846,0.00118755,0.00004619066,0.0004572802,0.4356304,0.001161153,0.0005042743,0.01489431,0.3435979,0.00007561407],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6154164,0.0136147,0.003512593,0.1740413,0.0006776655,0.0001419259,0.003665697,0.0001527366,0.1887769],"genre_scores_gemma":[0.9727194,0.009866226,0.001543083,0.004126071,0.0005070178,0.00008227789,0.0008092612,0.00004520132,0.01030155],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9976011,"threshold_uncertainty_score":0.08147508,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07665338017943327,"score_gpt":0.3712184149290081,"score_spread":0.2945650347495749,"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."}}