{"id":"W1589912152","doi":"10.15353/joci.v10i3.3436","title":"Community Informatics in Cities: New Catalysts for Urban Change","year":2014,"lang":"en","type":"article","venue":"The Journal of Community Informatics","topic":"E-Government and Public Services","field":"Social Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Informatics; Urban community; Geography; Regional science; Political science; Data science; Sociology; Computer science; Socioeconomics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.01396849,0.000133879,0.0003072461,0.0001614153,0.001397818,0.000179788,0.002232516,0.0001132025,0.00001929491],"category_scores_gemma":[0.0009126362,0.00009694743,0.00009810016,0.0003488173,0.0002841049,0.001892683,0.0002579219,0.001276842,0.000009764721],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001716286,"about_ca_system_score_gemma":0.0002312048,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01245149,"about_ca_topic_score_gemma":0.01657292,"domain_scores_codex":[0.9966575,0.001385219,0.001012555,0.000004526626,0.0006249136,0.0003152937],"domain_scores_gemma":[0.9956174,0.002306144,0.001149239,0.0005080443,0.0002635588,0.0001556116],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00003658822,0.00005800848,0.001481174,0.0001286163,0.00002296664,1.160161e-8,0.9732312,0.00002130587,5.458173e-7,0.004403355,0.01543438,0.005181874],"study_design_scores_gemma":[0.0007232781,0.0002078105,0.001855527,0.0001007295,0.0000389694,0.000004149418,0.8299657,0.0003046286,0.00001804989,0.004773336,0.1618921,0.0001157604],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9461185,0.00006565525,0.0009800427,0.004105619,0.0003047838,0.0003479921,0.00001150579,0.00002236148,0.04804352],"genre_scores_gemma":[0.9955989,0.0001673561,0.0004839478,0.003208637,0.0002917875,0.000003349836,0.00001298807,0.000007758037,0.0002252588],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1464577,"threshold_uncertainty_score":0.9999022,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08299093750856396,"score_gpt":0.3214452942165756,"score_spread":0.2384543567080116,"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."}}