{"id":"W248148568","doi":"","title":"Roughly Right or Precisely Wrong","year":2002,"lang":"en","type":"preprint","venue":"eScholarship (California Digital Library)","topic":"Smart Parking Systems Research","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Transit (satellite); Transport engineering; Trip generation; Quarter (Canadian coin); Dependency (UML); Public transport; Engineering; Computer science; Geography; Artificial intelligence","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":[0.005598448,0.001128479,0.0007783756,0.002481633,0.00265282,0.0100158,0.001161514,0.003471228,0.05729014],"category_scores_gemma":[0.05191689,0.0007239946,0.0005533432,0.001709577,0.009616021,0.01557953,0.003065379,0.003387952,0.01759914],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003025642,"about_ca_system_score_gemma":0.001783784,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0123433,"about_ca_topic_score_gemma":0.009257402,"domain_scores_codex":[0.9928368,0.002587679,0.0004994237,0.00205985,0.001519759,0.0004964046],"domain_scores_gemma":[0.9868425,0.00504222,0.001459542,0.002629524,0.003409954,0.0006163175],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004171307,0.00004165896,0.0205505,0.0003827217,0.0001287434,0.0005347507,0.007359828,0.001854416,0.0008882784,0.634296,0.1989381,0.1346079],"study_design_scores_gemma":[0.00005523939,0.00006651967,0.009510152,0.000664179,0.00008144544,0.0007200491,0.01140415,0.002968218,0.001867777,0.5306574,0.4418563,0.0001484135],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.05361865,0.01263184,0.107162,0.1515654,0.009152201,0.000112837,0.00384425,0.002022218,0.6598905],"genre_scores_gemma":[0.8305427,0.00581627,0.02262547,0.0261595,0.002162003,0.00009597084,0.002038238,0.001051979,0.1095078],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.05729014,"threshold_uncertainty_score":0.1916546,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02828267411858746,"score_gpt":0.2341406811236841,"score_spread":0.2058580070050966,"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."}}