{"id":"W2084756478","doi":"10.1080/01490400.2010.488199","title":"Looking Back in Time: The Pitfalls and Potential of Retrospective Methods in Leisure Studies","year":2010,"lang":"en","type":"article","venue":"Leisure Sciences","topic":"Recreation, Leisure, Wilderness Management","field":"Psychology","cited_by":59,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Psychology; Sociology; Computer science","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":[],"consensus_categories":[],"category_scores_codex":[0.004662482,0.0001705526,0.0004071401,0.0002655132,0.0001387299,0.00007375403,0.0005547741,0.0001099767,0.0003868168],"category_scores_gemma":[0.0001699975,0.0001147912,0.00004811656,0.0009137062,0.001155431,0.0002237687,0.0001790469,0.0003422155,0.00003227021],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002848304,"about_ca_system_score_gemma":0.00003734226,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004908522,"about_ca_topic_score_gemma":0.001073156,"domain_scores_codex":[0.9977869,0.0005343161,0.000401932,0.0005411329,0.0004011123,0.0003345942],"domain_scores_gemma":[0.9989616,0.0003608817,0.0002272351,0.0003321663,0.00008600028,0.00003206571],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001653279,0.00007634715,0.9761223,0.00001615105,0.00004070068,0.000005856251,0.003452273,0.00007379265,0.002280882,0.011494,0.00018261,0.006238574],"study_design_scores_gemma":[0.0004331,0.00009967863,0.9888339,0.0000477779,0.00001962946,0.000006235422,0.002304122,0.0001962454,0.0004315746,0.006902195,0.0005849284,0.0001405863],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9848807,0.0006969517,0.0003152594,0.001080204,0.0008304281,0.0005124183,0.000002030853,0.00001376982,0.01166825],"genre_scores_gemma":[0.9937621,0.00006371401,0.004648295,0.00001055991,0.0001014905,0.00003576371,6.764234e-7,0.00001001157,0.001367325],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01271164,"threshold_uncertainty_score":0.4681049,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03189480444823505,"score_gpt":0.4019049069957056,"score_spread":0.3700101025474705,"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."}}