{"id":"W4394322655","doi":"10.6084/m9.figshare.3515597","title":"Appendix A. List of social survey questions used to address movement potential of anglers in Ontario, Canada (taken from online questionnaire).","year":2016,"lang":"en","type":"dataset","venue":"Figshare","topic":"Recreation, Leisure, Wilderness Management","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Movement (music); Geography; Computer science; Data science","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":[0.0009126033,0.001241799,0.001147222,0.003352785,0.001620105,0.001928455,0.001961194,0.0009567268,0.1461268],"category_scores_gemma":[0.007308965,0.0007750951,0.0008082672,0.008392568,0.0005341488,0.0008448355,0.001218565,0.001044897,0.07455589],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01005453,"about_ca_system_score_gemma":0.01374888,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8431358,"about_ca_topic_score_gemma":0.9380116,"domain_scores_codex":[0.9992726,0.00005732628,0.00009451597,0.0001627135,0.0002498788,0.0001629443],"domain_scores_gemma":[0.9919594,0.001247295,0.0004894354,0.0005305362,0.005047426,0.0007258775],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002653858,0.00001556593,0.002882131,0.0003429055,0.000009115694,0.00001105617,0.00003175167,0.000105513,0.00002633446,0.0000923109,0.9949505,0.001506136],"study_design_scores_gemma":[0.0002901589,0.00002071692,0.06924765,0.0007215865,0.00004133535,0.00005662932,0.0004019075,0.0003981908,0.0002051279,0.00046564,0.9280999,0.0000511819],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001054426,0.00001553199,0.00002907506,0.00001943832,0.00000769064,0.00002932907,0.9992931,0.00003368812,0.0004666854],"genre_scores_gemma":[0.0006353338,0.0000428757,0.0001799133,0.00002844853,0.00000539539,0.0002698455,0.9971887,0.0000203322,0.001629118],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1568642,"threshold_uncertainty_score":0.4888427,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05026342456298528,"score_gpt":0.3107645029946791,"score_spread":0.2605010784316938,"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."}}