{"id":"W3108814614","doi":"10.24193/subbgeogr.2019.2.03","title":"Gentrification and Place Identity Change in Gheorgheni, City of Cluj-Napoca","year":2020,"lang":"en","type":"article","venue":"Studia Universitatis Babeș-Bolyai Geographia","topic":"Urbanization and City Planning","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Gentrification; Neighbourhood (mathematics); Identity (music); Economic geography; Sociology; Place identity; Quarter (Canadian coin); Geography; Political science; Gender studies; Economic growth; Urban planning; Civil engineering; Archaeology; Economics; Aesthetics; Art","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003172825,0.0001061217,0.0001978486,0.0002324004,0.000314127,0.00003792058,0.0002199246,0.00008533831,0.0002007212],"category_scores_gemma":[0.0001538633,0.0001304632,0.00004771331,0.001733527,0.0002818812,0.0006506231,0.00008445878,0.0001196961,0.000008071578],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003904755,"about_ca_system_score_gemma":0.00006670289,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003859286,"about_ca_topic_score_gemma":0.008187892,"domain_scores_codex":[0.9988007,0.0001884668,0.0001778429,0.0002731005,0.0003336176,0.0002262742],"domain_scores_gemma":[0.9993803,0.0001055165,0.0001371375,0.00009093669,0.0001294991,0.0001566167],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000452147,0.00006188411,0.8537567,0.00002937595,0.00005137046,0.00001100525,0.07808013,0.000005510897,0.0001240684,0.06563447,0.001264363,0.0009359252],"study_design_scores_gemma":[0.0009136872,0.00007379773,0.9542912,0.00002810415,0.00005528536,2.344185e-7,0.03242248,0.00008129072,0.00002544797,0.0003985574,0.01150107,0.0002088228],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9855627,0.001005166,0.0003664905,0.003954488,0.0001257899,0.0004510994,0.0000446412,0.00007061921,0.008418971],"genre_scores_gemma":[0.9982804,0.0009299334,0.0003269627,0.0003244627,0.00005554144,0.000003299738,0.00001704633,0.000006278113,0.00005607258],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1005345,"threshold_uncertainty_score":0.5834112,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04178597923899091,"score_gpt":0.287387477365624,"score_spread":0.2456014981266331,"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."}}