{"id":"W4414182174","doi":"10.3390/land14091880","title":"Research on the Priority of County-Level Territorial Space Consolidation: Form–Flow Synthesis Analysis Based on Principal Component Analysis","year":2025,"lang":"en","type":"article","venue":"Land","topic":"Land Use and Ecosystem Services","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute on Governance","funders":"Zhejiang University; National Natural Science Foundation of China","keywords":"Principal component analysis; Space (punctuation); Consolidation (business); Matching (statistics); Identification (biology); Corporate governance","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002997368,0.0003936598,0.0005531663,0.005672342,0.0009197347,0.003733021,0.0004337394,0.0003363412,0.00216494],"category_scores_gemma":[0.007986748,0.0001912414,0.0005030109,0.00669061,0.001364335,0.003941697,0.00141723,0.0004840364,0.0001109668],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002038289,"about_ca_system_score_gemma":0.002873023,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005594064,"about_ca_topic_score_gemma":0.006116424,"domain_scores_codex":[0.9980519,0.0007984471,0.0001790747,0.0003355513,0.0004691519,0.0001659551],"domain_scores_gemma":[0.9967192,0.00116964,0.000512368,0.0002792437,0.001180362,0.0001392741],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0002242284,0.0001656665,0.3105125,0.0010735,0.0003889384,0.0001708306,0.008724748,0.02214655,0.007019441,0.2148452,0.002281018,0.4324474],"study_design_scores_gemma":[0.00006467856,0.000430012,0.6012342,0.0004248624,0.0007134308,0.0002569545,0.0472367,0.1629903,0.01201305,0.1471156,0.02734613,0.0001740996],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7046217,0.0007980156,0.2759819,0.0007353225,0.00005755408,0.0004375057,0.0004215518,0.0001935452,0.01675292],"genre_scores_gemma":[0.9657634,0.0002387446,0.03303485,0.00002087156,0.00001168791,0.0001189002,0.0001958214,0.00001546408,0.0006001386],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005672342,"threshold_uncertainty_score":0.0158518,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03517613007924512,"score_gpt":0.2986721731040148,"score_spread":0.2634960430247697,"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."}}