{"id":"W7103235168","doi":"","title":"A turizmus 1995 és 2021 közötti karbonhatékonyságának vizsgálata hazánkban az egyes üvegházhatású gázok szerinti bontásban = Evaluation of the carbon-efficiency in tourism for
\\nthe different greenhouse gases
\\nbetween 1995 and 2021 in Hungary","year":2024,"lang":"hu","type":"article","venue":"Repository of the Academy's Library (Library of the Hungarian Academy of Sciences)","topic":"Agriculture Sustainability and Environmental Impact","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Greenhouse gas; Carbon credit; Carbon fibers; Tourism; Methane; Nitrogen","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":[0.0003777382,0.0002236512,0.0002344345,0.0008083301,0.0002528623,0.001900697,0.0003352737,0.0003376717,0.007913182],"category_scores_gemma":[0.0006182813,0.0001257896,0.0003357791,0.001823078,0.0002198334,0.0005047703,0.0005950159,0.0003595563,0.001210244],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004566255,"about_ca_system_score_gemma":0.002736675,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.223704,"about_ca_topic_score_gemma":0.2130218,"domain_scores_codex":[0.9997169,0.00001591721,0.00002280719,0.0000536495,0.0001171486,0.00007355509],"domain_scores_gemma":[0.9997291,0.00002861372,0.00006648253,0.00001322194,0.0001198695,0.00004266962],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003822114,0.0002730046,0.5371958,0.002826577,0.0004402526,0.001610962,0.002156696,0.01497081,0.007622286,0.01707971,0.2027187,0.2092832],"study_design_scores_gemma":[0.00005565956,0.00008008162,0.8725154,0.0001230515,0.00008291764,0.00008127293,0.002378681,0.001503989,0.002899424,0.0005007818,0.1197555,0.0000232656],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7510211,0.004460803,0.001062314,0.002398149,0.0001920303,0.0001206984,0.1993383,0.0001789329,0.04122751],"genre_scores_gemma":[0.8491126,0.003285724,0.001395418,0.0003956061,0.00004285752,0.00008039779,0.1077226,0.00006771432,0.03789714],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.223704,"threshold_uncertainty_score":0.4448038,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01538301228695363,"score_gpt":0.2422350016060394,"score_spread":0.2268519893190858,"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."}}