{"id":"W2724616130","doi":"10.24306/plnxt.2017.04.006","title":"Delving deeper","year":2017,"lang":"en","type":"article","venue":"plaNext - Next Generation Planning","topic":"Smart Cities and Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Cityscape; Agency (philosophy); Public space; Architectural engineering; Metropolitan area; Democracy; Smart city; Space (punctuation); Sociology; Regional science; Political science; Computer science; Engineering; Geography; Social science; Computer security","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007484909,0.0001370485,0.0001214217,0.00007190193,0.0005544427,0.0004988766,0.0002549742,0.0001085909,0.00009522786],"category_scores_gemma":[0.00006509142,0.0001391657,0.00002836078,0.0000237981,0.00003373183,0.0004651081,0.00004972485,0.0001466757,0.00008684617],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002729445,"about_ca_system_score_gemma":0.000006989871,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002119516,"about_ca_topic_score_gemma":0.00002332599,"domain_scores_codex":[0.9993469,0.000005594851,0.0001516815,0.0001480466,0.0001106724,0.0002371358],"domain_scores_gemma":[0.9994839,0.0000272833,0.00004448627,0.0003859956,0.00001825497,0.00004002258],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001737227,0.0000279541,0.05728409,0.0001443862,0.0002464282,0.0002718786,0.002194986,0.3177058,0.3557465,0.01127735,0.1797072,0.07537602],"study_design_scores_gemma":[0.0006030508,0.00005022926,0.01356013,0.0001082047,0.0000351403,0.00009501568,0.0007546658,0.8102448,0.05446782,0.0006849939,0.118485,0.0009109873],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9727718,0.001072059,0.007817343,0.0001352746,0.001256041,0.00008755691,0.00001140783,0.0008849197,0.01596366],"genre_scores_gemma":[0.9960352,0.00007588775,0.003019596,0.00006121774,0.0005037893,0.00001753283,0.00006308775,0.0000250217,0.0001986944],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.492539,"threshold_uncertainty_score":0.5675013,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0879242361959855,"score_gpt":0.2562574197027219,"score_spread":0.1683331835067364,"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."}}