{"id":"W7133382163","doi":"","title":"Introduction","year":2022,"lang":"en","type":"other","venue":"RUNE (Research UNE)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Human settlement; Population; Boom; Settlement (finance); State (computer science); Rural area; Government (linguistics)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.002271434,0.0008845368,0.0007091759,0.001620682,0.00321526,0.008379982,0.002846643,0.00363432,0.477553],"category_scores_gemma":[0.009631086,0.0003650735,0.0008170801,0.002053094,0.001640202,0.005875818,0.005506523,0.003365904,0.302076],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003607115,"about_ca_system_score_gemma":0.005156181,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007013881,"about_ca_topic_score_gemma":0.006385643,"domain_scores_codex":[0.9969372,0.0005818382,0.000180146,0.0006830305,0.001230707,0.0003870912],"domain_scores_gemma":[0.9960706,0.0005799122,0.0001880759,0.0005937315,0.001874651,0.0006930213],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005870278,0.00004847251,0.0008284499,0.0003370192,0.000007094367,0.0001699349,0.001100338,0.00007442413,0.0002050081,0.04906838,0.8359963,0.112106],"study_design_scores_gemma":[0.000003263588,0.000009076102,0.0003676767,0.0001378723,0.000001678273,0.0000965721,0.0003537487,0.00002007145,0.00005112224,0.002778967,0.9961751,0.000004880321],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.001965915,0.004075756,0.00484708,0.01990849,0.0114683,0.000340026,0.00608775,0.001047512,0.9502591],"genre_scores_gemma":[0.01986067,0.004252477,0.004367419,0.01629841,0.002426103,0.0004286478,0.007816339,0.0008085719,0.9437414],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.522447,"threshold_uncertainty_score":0.7452073,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07592908229059539,"score_gpt":0.3999527002716143,"score_spread":0.3240236179810189,"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."}}