{"id":"W4396909045","doi":"10.11118/978-80-7509-963-1-0277","title":"REDUCING THE NEGATIVE IMPACT OF TOURISM ON THE ENVIRONMENT BY USING RAIL TRANSPORT. CASE STUDY: BUCHAREST NORD-BRASOV ROUTE","year":2024,"lang":"en","type":"article","venue":"Public recreation and landscape protection ...","topic":"transportation and logistics systems","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Tourism; Road transport; Greenhouse gas; European union; Public transport; Mode of transport; Transport engineering; Quarter (Canadian coin); Environmental science; Business; Environmental economics; Environmental planning; Engineering; Geography; International trade; Economics","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":[0.0003406032,0.0004284524,0.00022359,0.0007886209,0.002356439,0.001191244,0.000766303,0.001254872,0.00390994],"category_scores_gemma":[0.0004131812,0.0001429734,0.0004664608,0.001438539,0.0008478408,0.0006725313,0.0009240765,0.0005531268,0.0003812434],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001929868,"about_ca_system_score_gemma":0.001485501,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05745534,"about_ca_topic_score_gemma":0.1301619,"domain_scores_codex":[0.9997353,0.0001062829,0.000008764302,0.00001724188,0.00003636137,0.00009599351],"domain_scores_gemma":[0.9998173,0.0000719009,0.00001998151,0.00001199762,0.00003383165,0.00004499241],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"case_report","study_design_gemma":"observational","study_design_scores_codex":[0.001652532,0.005998778,0.1423521,0.003828696,0.0003885116,0.2506568,0.04409564,0.1856925,0.01943185,0.08955067,0.03511986,0.2212322],"study_design_scores_gemma":[0.0003768344,0.005273588,0.2010672,0.001268367,0.0004096106,0.02402439,0.4029639,0.05505013,0.01535342,0.01135154,0.2825944,0.0002667776],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9682736,0.0006199713,0.001410158,0.0004380748,0.00003140809,0.000165816,0.0003332129,0.00002342259,0.02870432],"genre_scores_gemma":[0.98318,0.001089835,0.002391505,0.00004838871,0.00000719297,0.00007206624,0.0002031715,0.00001284569,0.01299496],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05745534,"threshold_uncertainty_score":0.1142418,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06815725348897525,"score_gpt":0.3182147354590443,"score_spread":0.2500574819700691,"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."}}