{"id":"W2372624215","doi":"","title":"Parking lots planning in residential quarters","year":2003,"lang":"en","type":"article","venue":"Shanxi Architecture","topic":"Smart Parking Systems Research","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Quarter (Canadian coin); Transport engineering; Measure (data warehouse); Parking guidance and information; Pedestrian; Parking lot; Engineering; Computer science; Civil engineering; Geography","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":[0.0003806823,0.0001636675,0.0001718746,0.0005327374,0.0009248758,0.0007716748,0.0004971142,0.000349398,0.004576053],"category_scores_gemma":[0.0005218026,0.000288052,0.0002753812,0.0006131221,0.0002973378,0.0007980228,0.0005258792,0.0002621933,0.0006031604],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008003936,"about_ca_system_score_gemma":0.001048366,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006600925,"about_ca_topic_score_gemma":0.0138351,"domain_scores_codex":[0.9997134,0.0001143721,0.00001277185,0.00003881749,0.00004785701,0.00007273804],"domain_scores_gemma":[0.9998168,0.00002312035,0.00003024417,0.00002348422,0.00006405102,0.00004226382],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0008578175,0.0002731719,0.06893679,0.0005092293,0.00006183935,0.002000205,0.002509552,0.2333993,0.0166019,0.07274158,0.02201849,0.58009],"study_design_scores_gemma":[0.00007307963,0.0009565087,0.08416234,0.0001218193,0.0001054337,0.002662432,0.01324588,0.6961488,0.02289446,0.08523111,0.0942347,0.0001634235],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8069656,0.001655104,0.1473498,0.001214618,0.0001243589,0.0001267067,0.0003780691,0.0009849262,0.04120089],"genre_scores_gemma":[0.9780227,0.0002273029,0.01340298,0.00002001645,0.00000722771,0.00001249726,0.0001157375,0.00002283862,0.008168711],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006600925,"threshold_uncertainty_score":0.01530844,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01236662184491548,"score_gpt":0.2500508620902701,"score_spread":0.2376842402453546,"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."}}