{"id":"W2787812477","doi":"10.55016/ojs/sppp.v10i1.43058","title":"Big and Little Feet Provincial Profiles: Nova Scotia","year":2017,"lang":"en","type":"article","venue":"The School of Public Policy Publications","topic":"Environmental Impact and Sustainability","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Alberta Innovates","keywords":"Nova scotia; Nova (rocket); Geography; Forestry; Archaeology; Aeronautics; Engineering","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.00025412,0.0005015463,0.0003038745,0.003612828,0.002100552,0.00225896,0.0005654751,0.0003630122,0.02554364],"category_scores_gemma":[0.001021628,0.0003044678,0.000452954,0.01087268,0.0003435596,0.0004879939,0.001309179,0.0005745323,0.004663409],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01597492,"about_ca_system_score_gemma":0.0268269,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9856368,"about_ca_topic_score_gemma":0.9942266,"domain_scores_codex":[0.9994302,0.00001920698,0.00003388409,0.00008696259,0.0002027177,0.0002270393],"domain_scores_gemma":[0.9986814,0.00004697691,0.0001258033,0.00008366222,0.0007961956,0.0002659523],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0006416154,0.00006869721,0.2787268,0.001446795,0.0001769964,0.001643645,0.007011156,0.002989805,0.0051724,0.01528405,0.5566683,0.1301697],"study_design_scores_gemma":[0.00002460258,0.00002383156,0.4901588,0.0002838006,0.00002972356,0.0002216355,0.004664883,0.0008694173,0.0008395629,0.0005581458,0.5022604,0.00006526284],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.1551971,0.003105145,0.001069995,0.002008438,0.000496888,0.0003188,0.6358148,0.0006393935,0.2013494],"genre_scores_gemma":[0.4462105,0.003679754,0.004255338,0.0007275896,0.0001016493,0.0002496733,0.2729189,0.0006501106,0.2712065],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02554364,"threshold_uncertainty_score":0.1159067,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03467156095867403,"score_gpt":0.3051083362248945,"score_spread":0.2704367752662205,"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."}}