{"id":"W4413728328","doi":"10.64628/aam.y7w6psqad","title":"What if MIT’s Norman and Amazon’s Alexa hooked up?","year":2018,"lang":"ru","type":"preprint","venue":"","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Amazon rainforest; Alexa Fluor; Art; Geography; Physics; Biology; Ecology; Optics","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":[0.003222258,0.000410239,0.0005694881,0.001778937,0.005879764,0.01069585,0.0008695306,0.0058538,0.05874841],"category_scores_gemma":[0.03267993,0.0003415266,0.0006628004,0.001988654,0.003346568,0.01581217,0.002142067,0.006053788,0.0207638],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004376006,"about_ca_system_score_gemma":0.00582903,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04199806,"about_ca_topic_score_gemma":0.05980982,"domain_scores_codex":[0.9963359,0.0006942525,0.0001141333,0.0004494695,0.001326728,0.001079618],"domain_scores_gemma":[0.9873036,0.002022209,0.00101633,0.001005473,0.005165495,0.003486869],"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":[0.0001791162,0.00009660578,0.01413839,0.00009561314,0.0000454105,0.0002592808,0.0009556095,0.00009749458,0.0003953538,0.08251868,0.8463985,0.05481988],"study_design_scores_gemma":[0.00004110481,0.00005171461,0.02464724,0.0004531479,0.00007711673,0.0003001296,0.01116037,0.0005279621,0.001151619,0.05706055,0.9044039,0.0001252191],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"other","genre_scores_codex":[0.03219057,0.002729954,0.001743703,0.7243079,0.01167284,0.0000356191,0.001876922,0.0008322206,0.2246102],"genre_scores_gemma":[0.5280437,0.003180812,0.003454573,0.2255653,0.005989295,0.00009663565,0.002116105,0.001696638,0.229857],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.05874841,"threshold_uncertainty_score":0.196533,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06511519208003731,"score_gpt":0.2908606845110461,"score_spread":0.2257454924310088,"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."}}