{"id":"W3041458194","doi":"","title":"Triangulating Neighborhoods: A Research Note on Improving Links Between People and Places in Smaller Cities and Rural Areas","year":2020,"lang":"en","type":"article","venue":"Journal of rural and community development","topic":"Urban, Neighborhood, and Segregation Studies","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Geocoding; Neighbourhood (mathematics); Geospatial analysis; Field (mathematics); Code (set theory); Space (punctuation); Geography; Data science; Regional science; Sociology; Public relations; Computer science; Cartography; Political science; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.002503866,0.0001164705,0.0003229951,0.0001529763,0.001669473,0.0001853816,0.0001680991,0.0001007095,0.00001072501],"category_scores_gemma":[0.0007923881,0.00009210958,0.00002583455,0.0002547075,0.0002095898,0.0002448984,0.0002238525,0.001226503,7.22439e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007977943,"about_ca_system_score_gemma":0.0002036627,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002028875,"about_ca_topic_score_gemma":0.003204495,"domain_scores_codex":[0.9979389,0.0008941523,0.0004084191,0.00006382387,0.0004389225,0.0002557976],"domain_scores_gemma":[0.9978029,0.001595375,0.0001774199,0.00005315141,0.0001815454,0.0001896053],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0001480291,0.00003404698,0.3229568,0.00005640966,0.0000524391,0.000003705911,0.5059763,0.000003210448,0.00003979496,0.000270321,0.0000794583,0.1703795],"study_design_scores_gemma":[0.0008284222,0.0002613538,0.6870438,0.0002064442,0.000009526206,0.000003086164,0.309822,0.00005290512,0.00003670997,0.0006784787,0.0009302616,0.0001270226],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9918859,0.0007957648,0.00003004299,0.006117539,0.00004150865,0.0001223895,0.00000174293,0.00000937974,0.0009957282],"genre_scores_gemma":[0.9986246,0.0006068854,0.0003474958,0.0001527607,0.0001602171,0.000003174095,0.000001287481,0.000005766037,0.00009777818],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.364087,"threshold_uncertainty_score":0.9996302,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1070959408745783,"score_gpt":0.3460698930185375,"score_spread":0.2389739521439592,"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."}}