{"id":"W4405911631","doi":"10.54033/cadpedv21n13-435","title":"Scientific production on environmental education: a bibliometric analysis","year":2024,"lang":"en","type":"article","venue":"Caderno Pedagógico","topic":"Environmental Sustainability and Education","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Production (economics); Bibliometrics; Computer science; Library science; 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":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.007661744,0.0006715604,0.001649909,0.1712836,0.001620151,0.006146306,0.000703893,0.0006721305,0.003486564],"category_scores_gemma":[0.03630675,0.0002667262,0.001813654,0.2449509,0.001156791,0.003868647,0.0033089,0.0004270951,0.0007643008],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002789462,"about_ca_system_score_gemma":0.004593151,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004990112,"about_ca_topic_score_gemma":0.0042681,"domain_scores_codex":[0.9833891,0.003079442,0.002244154,0.0009310601,0.009727987,0.0006282424],"domain_scores_gemma":[0.9676749,0.01999494,0.004549787,0.001443265,0.005799687,0.0005374964],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002731259,0.000261381,0.5403432,0.009992681,0.001894922,0.0009202313,0.008832519,0.006409767,0.003267125,0.01235831,0.01548565,0.3999611],"study_design_scores_gemma":[0.00004879831,0.0002731112,0.8719558,0.002098626,0.001347369,0.001493542,0.01364214,0.01218615,0.002863188,0.00686498,0.08707435,0.0001519274],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8414995,0.02983347,0.01141864,0.002625644,0.000322247,0.0007462424,0.03549891,0.0007104049,0.07734507],"genre_scores_gemma":[0.9617398,0.01364477,0.009565336,0.00006331795,0.0003100362,0.0004035532,0.0120881,0.00008259123,0.002102484],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8287164,"threshold_uncertainty_score":0.04051965,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01406331207928111,"score_gpt":0.2773198190594967,"score_spread":0.2632565069802156,"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."}}