{"id":"W7116630511","doi":"10.31407/ijees15.636","title":"LEVERAGING THE WILDLIFE INSIGHTS PLATFORM TO BUILD AI LITERACY AND ANALYTICAL SKILLS IN FUTURE ENVIRONMENTAL SPECIALISTS","year":2025,"lang":"","type":"article","venue":"International Journal of Ecosystems and Ecology Science (IJEES)","topic":"Architecture and Computational Design","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Literacy; Citizen science; Wildlife; Digital literacy; Sustainability; Government (linguistics)","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":[0.001357869,0.0002887008,0.0001656503,0.0006064028,0.0004691225,0.0008292221,0.0005681802,0.000448216,0.003354579],"category_scores_gemma":[0.002719689,0.000168889,0.0002671742,0.0001721732,0.0003929171,0.0007557091,0.001988481,0.0005715556,0.0006964905],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003410625,"about_ca_system_score_gemma":0.00186622,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006514266,"about_ca_topic_score_gemma":0.002290061,"domain_scores_codex":[0.999529,0.0001684195,0.00002113754,0.0000806645,0.0001011165,0.00009971399],"domain_scores_gemma":[0.9988083,0.0004127668,0.0001225812,0.0001055312,0.0001311594,0.0004195521],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005923713,0.01825775,0.09191627,0.0004962313,0.00003722338,0.001164799,0.01611375,0.002007239,0.09127186,0.002674404,0.004641984,0.7708262],"study_design_scores_gemma":[0.0007076791,0.0296374,0.6965678,0.0009744294,0.0002795512,0.003884298,0.02501908,0.02010381,0.08742194,0.01346569,0.121679,0.0002593345],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9819797,0.00007878292,0.0108488,0.0005368024,0.00002322613,0.0002753426,0.00002774263,0.0001202614,0.006109473],"genre_scores_gemma":[0.9014166,0.0002625831,0.09147368,0.0003084489,0.00002603095,0.0004439166,0.0001159567,0.00001699831,0.005935875],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003354579,"threshold_uncertainty_score":0.01122218,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004285996383576472,"score_gpt":0.2497482056248423,"score_spread":0.2454622092412659,"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."}}