{"id":"W2096912489","doi":"10.3368/er.31.4.412","title":"Using Problem-based Learning to Teach Concepts for Ecological Restoration","year":2013,"lang":"en","type":"article","venue":"Ecological Restoration","topic":"Conservation, Ecology, Wildlife Education","field":"Environmental Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Restoration ecology; Ecology; Mathematics education; Computer science; Psychology; Biology","routes":{"ca_aff":true,"ca_fund":false,"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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0009212676,0.0002036568,0.0002198352,0.00008210724,0.0005910504,0.0001288657,0.000218,0.0002984675,0.003801026],"category_scores_gemma":[0.002920201,0.0001869159,0.00006696059,0.0004097992,0.0001434364,0.0005959572,0.0000881878,0.0002292409,0.001043105],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001234989,"about_ca_system_score_gemma":0.0001155399,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001526409,"about_ca_topic_score_gemma":0.0006449143,"domain_scores_codex":[0.9978465,0.0003655135,0.0004927835,0.0005834492,0.0002786735,0.0004330166],"domain_scores_gemma":[0.9986388,0.0005629446,0.000266494,0.0002105759,0.0001201525,0.0002010004],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00010381,0.0008393629,0.681027,0.00001892087,0.00001068386,0.000001641259,0.0005305307,0.1977352,0.05529597,0.0007570296,0.05829927,0.005380597],"study_design_scores_gemma":[0.0004223684,0.000872586,0.9083959,0.00000690624,0.0000143037,0.000001588768,0.0001316947,0.05343708,0.0002509595,0.001673713,0.03452756,0.000265313],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9669428,0.000003826131,0.02192361,0.007302374,0.0003539595,0.002555961,0.000002244995,0.000156013,0.0007591361],"genre_scores_gemma":[0.9339338,9.138423e-7,0.06176906,0.002123023,0.0001764282,0.001193401,0.00008816083,0.00001758573,0.0006976624],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2273689,"threshold_uncertainty_score":0.9997347,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05738457419912783,"score_gpt":0.3314970612500067,"score_spread":0.2741124870508789,"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."}}