{"id":"W155991542","doi":"10.12794/metadc271888","title":"Using Progressive Ratio Schedules to Evaluate Edible, Leisure, and Token Reinforcement","year":2013,"lang":"en","type":"dissertation","venue":"","topic":"Behavioral and Psychological Studies","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Global Affairs Canada","funders":"","keywords":"Reinforcement; Security token; Psychology; Computer science; Social psychology; Computer network","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001037103,0.0007785285,0.0002484257,0.0005866734,0.000259665,0.0002052345,0.0004744548,0.000324649,0.001892536],"category_scores_gemma":[0.002646071,0.000237657,0.0002333184,0.0002853707,0.0005691682,0.0003560565,0.0004383948,0.00107116,0.0001710418],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003991472,"about_ca_system_score_gemma":0.0005084933,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001307812,"about_ca_topic_score_gemma":0.002546843,"domain_scores_codex":[0.9989787,0.0003565382,0.00008051536,0.0001429768,0.0003668935,0.00007436093],"domain_scores_gemma":[0.9981541,0.00066823,0.000552645,0.0001831801,0.0001787757,0.0002631817],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.01126581,0.01660851,0.03078933,0.0004099998,0.000115349,0.0003787048,0.001315701,0.001236641,0.8673205,0.001517861,0.0002996429,0.06874188],"study_design_scores_gemma":[0.001368895,0.1334039,0.3177788,0.00005414582,0.0001656306,0.001584545,0.0009967147,0.00598443,0.5341116,0.001136112,0.003319347,0.00009597014],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9932011,0.00007916335,0.004698462,0.00001540627,0.000009441406,0.0004696151,0.0000991003,0.00003717995,0.001390545],"genre_scores_gemma":[0.9639205,0.0002698148,0.03048779,0.00005258321,0.00001274461,0.001735326,0.0002607325,0.00004301547,0.003217485],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001892536,"threshold_uncertainty_score":0.006331146,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2810359156115431,"score_gpt":0.4446609431511468,"score_spread":0.1636250275396037,"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."}}