{"id":"W4390948577","doi":"10.1080/01441647.2024.2305202","title":"Modelling parking behaviour of commercial vehicles: a scoping review","year":2024,"lang":"en","type":"review","venue":"Transport Reviews","topic":"Smart Parking Systems Research","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Transport engineering; Parking guidance and information; Economic shortage; Commercial vehicle; Service (business); Park and ride; Car parking; Business; Engineering; Marketing; Public transport; Government (linguistics)","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002605769,0.0009555451,0.007025155,0.0003988917,0.00005533962,0.00003175849,0.0008291401,0.0004080056,0.0001083828],"category_scores_gemma":[0.00002113081,0.0007654046,0.002163943,0.001174027,0.00006595327,0.0001102924,0.00004021202,0.001293781,0.0005025826],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001898093,"about_ca_system_score_gemma":0.0002846821,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005075814,"about_ca_topic_score_gemma":0.00003248505,"domain_scores_codex":[0.9938856,0.0003248154,0.003860519,0.0006553104,0.0006145793,0.0006592272],"domain_scores_gemma":[0.9981012,0.0001228984,0.000409638,0.001119018,0.00006369168,0.0001835117],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","study_design_scores_codex":[2.993272e-7,0.000009001953,0.000004549456,0.6355844,0.00009183367,0.00002848658,0.00004244332,0.0000968964,8.994267e-8,0.000006729435,0.0009654076,0.3631698],"study_design_scores_gemma":[0.00002398117,0.000006613524,1.200543e-7,0.5048189,0.001803264,0.00002272491,5.920281e-7,0.0001484785,2.779975e-7,7.999089e-7,0.4928568,0.0003174027],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.000001617095,0.9899993,0.001762007,0.000003700544,0.0007317673,0.006223443,0.00007810721,0.0003250561,0.0008750181],"genre_scores_gemma":[0.00001076129,0.9972554,0.0004700255,0.00001188761,0.0003530986,0.001270197,0.0001976827,0.0003183722,0.0001125038],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.4918914,"threshold_uncertainty_score":0.9994797,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.183468435183076,"score_gpt":0.4021593227262448,"score_spread":0.2186908875431688,"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."}}