{"id":"W3106923209","doi":"10.22148/001c.18120","title":"A Computational Approach to Urban Space in Science Fiction","year":2020,"lang":"en","type":"article","venue":"Journal of Cultural Analytics","topic":"Human Mobility and Location-Based Analysis","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Space (punctuation); Techno-thriller; Fiction theory; Point (geometry); Urban space; Urban planning; Literary fiction; Geography; Computer science; Regional science; Mathematics; Literature; Art; Literary criticism; Engineering; Civil engineering","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":[],"consensus_categories":[],"category_scores_codex":[0.0009165616,0.00005652394,0.0001542243,0.000155838,0.000265305,0.0001350016,0.0002722915,0.00003002714,0.0000381475],"category_scores_gemma":[0.0007214145,0.00004421458,0.00009058724,0.001764605,0.0002181348,0.0003661552,0.00001706072,0.0001612753,0.00001029847],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002229261,"about_ca_system_score_gemma":0.0003862535,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002734556,"about_ca_topic_score_gemma":0.000166044,"domain_scores_codex":[0.9986649,0.00007702815,0.0003066873,0.0001171013,0.0006860779,0.0001482665],"domain_scores_gemma":[0.9988866,0.00004841613,0.0001588939,0.00004172755,0.0006127668,0.0002515414],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005162221,0.0002383636,0.01646492,0.00001947757,0.00004762201,0.00000645581,0.1365971,0.8143839,0.0003651721,0.02035274,0.009914874,0.001557782],"study_design_scores_gemma":[0.001286786,0.000484724,0.0590757,0.0001094104,0.0002377326,0.0000109735,0.1670546,0.7047324,0.0001935098,0.003068915,0.06310336,0.0006419169],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9025424,0.00008996346,0.045981,0.03314259,0.0001335103,0.0001840297,0.000003223275,0.00002094298,0.01790237],"genre_scores_gemma":[0.9965641,0.000009202474,0.002402068,0.0005547196,0.0003153576,4.900087e-7,0.000001382678,0.000001807166,0.0001508234],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1096515,"threshold_uncertainty_score":0.2040538,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0469397853434405,"score_gpt":0.3225254073441537,"score_spread":0.2755856220007132,"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."}}