{"id":"W4226426977","doi":"10.5281/zenodo.6406784","title":"The Jane Finch TSNS Task Force. Community Response to the Toronto Strong Neighbourhoods Strategy 2020: What Neighbourhood Improvement Looks like from the Perspective of Residents in Jane / Finch","year":2022,"lang":"en","type":"report","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Social Sciences and Governance","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Strong","keywords":"Finch; Neighbourhood (mathematics); Perspective (graphical); Task force; Sociology; Task (project management); Geography; Ecology; Computer science; Political science; Biology; Management; Mathematics; Economics; Artificial intelligence; Public administration","routes":{"ca_aff":true,"ca_fund":false,"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":[0.008500882,0.001352265,0.0005904118,0.001411126,0.00471334,0.004538723,0.003969642,0.008754946,0.01522588],"category_scores_gemma":[0.00957308,0.0009629916,0.0006860335,0.002415367,0.002599328,0.001549772,0.00502731,0.005220336,0.003713424],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05152273,"about_ca_system_score_gemma":0.2124834,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9552726,"about_ca_topic_score_gemma":0.9721867,"domain_scores_codex":[0.9938946,0.0007196961,0.0003066811,0.0002845255,0.003096459,0.001698027],"domain_scores_gemma":[0.980296,0.001063121,0.0006726749,0.0002723127,0.006094015,0.01160193],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"qualitative","study_design_scores_codex":[0.00003690943,0.00001992634,0.001488279,0.00019431,0.000008103736,0.0000839188,0.0008325137,0.000169236,0.0001223103,0.002358851,0.9892637,0.005422023],"study_design_scores_gemma":[0.0001108397,0.00004771179,0.02329017,0.0009631352,0.0000357371,0.00004611785,0.005695454,0.0002080853,0.0003280123,0.0006282926,0.9685732,0.00007333785],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"other","genre_scores_codex":[0.0214188,0.02996912,0.00162793,0.6969182,0.01724096,0.003483667,0.05362715,0.0005539733,0.1751601],"genre_scores_gemma":[0.1438649,0.02266077,0.007826881,0.1235989,0.00238179,0.004535519,0.05685283,0.0006587392,0.6376198],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.05152273,"threshold_uncertainty_score":0.3738253,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04536472373350008,"score_gpt":0.3224821947716043,"score_spread":0.2771174710381042,"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."}}