{"id":"W6998591153","doi":"","title":"Aproximació a l'estudi de les migracions residencials a la regió metropolitana de Barcelona : els casos d'Alella i Matadepera","year":2004,"lang":"ca","type":"article","venue":"RACO (Revistes Catalanes amb Accés Obert) (Consorci de Serveis Universitaris de Catalunya)","topic":"Migration, Aging, and Tourism Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Population; Older people; State (computer science); Quarter (Canadian coin)","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":[],"consensus_categories":[],"category_scores_codex":[0.001472653,0.0002370293,0.0003058588,0.001152057,0.002401147,0.002088176,0.0009967383,0.0005729006,0.00482043],"category_scores_gemma":[0.003351261,0.0002630747,0.0002461298,0.001392883,0.0009561405,0.0005853461,0.002410608,0.0005677308,0.0006925239],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004085595,"about_ca_system_score_gemma":0.002899187,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1858224,"about_ca_topic_score_gemma":0.3022406,"domain_scores_codex":[0.9992365,0.0002967237,0.0000497245,0.0001216774,0.00009910583,0.000196417],"domain_scores_gemma":[0.998197,0.0004810466,0.0003574373,0.0000909146,0.0004400703,0.0004335626],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004208341,0.0002748057,0.7902347,0.000898842,0.00005397922,0.002541093,0.1375162,0.0003250014,0.001001879,0.002596156,0.01091427,0.05322211],"study_design_scores_gemma":[0.00002334276,0.0001817379,0.8196914,0.0003989555,0.00003043012,0.0004414952,0.139084,0.0001314714,0.0001700291,0.0001902953,0.03964024,0.00001649992],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.986673,0.002232929,0.000160615,0.002115803,0.0000611123,0.00006480794,0.0003454283,0.00001395947,0.008332368],"genre_scores_gemma":[0.9838635,0.001361552,0.0003892153,0.0005075279,0.0000448596,0.0001605737,0.000389787,0.00001037321,0.01327259],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1858224,"threshold_uncertainty_score":0.3694815,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01284465870283434,"score_gpt":0.2753373961425725,"score_spread":0.2624927374397381,"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."}}