{"id":"W4213443684","doi":"10.1073/pnas.2120180119","title":"Information overload and resilience in facing foundational issues","year":2022,"lang":"en","type":"letter","venue":"Proceedings of the National Academy of Sciences","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada; Government of Canada","keywords":"Information overload; Resilience (materials science); Computer science; Data science; Political science; Cognitive science; Psychology; World Wide Web; Physics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.01550883,0.0004826728,0.0007153841,0.001785069,0.004811816,0.006475502,0.001814662,0.01595576,0.006576544],"category_scores_gemma":[0.07959045,0.0004230036,0.0005148869,0.001414513,0.02237647,0.02136162,0.004712497,0.02270206,0.003098583],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005021667,"about_ca_system_score_gemma":0.002432795,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002307622,"about_ca_topic_score_gemma":0.002909897,"domain_scores_codex":[0.9928693,0.003305591,0.0003103333,0.001170816,0.001718982,0.0006250253],"domain_scores_gemma":[0.9061301,0.07826057,0.003419893,0.004689294,0.004255805,0.003244264],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001345098,0.00003541031,0.002294873,0.0002168815,0.00004689399,0.001046671,0.002690524,0.00060117,0.0002420347,0.4706376,0.4394712,0.08258222],"study_design_scores_gemma":[0.00003467735,0.00002253855,0.001086289,0.0002612455,0.00001092079,0.0006804519,0.0017526,0.001366596,0.0002006467,0.8002165,0.1943285,0.00003910169],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.001950303,0.002585785,0.003011069,0.982852,0.002836731,0.000007519185,0.00003613427,0.00002952269,0.006691003],"genre_scores_gemma":[0.3030468,0.01302907,0.006342881,0.6165281,0.04953565,0.0001951851,0.00009884162,0.0001570669,0.0110664],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.01595576,"threshold_uncertainty_score":0.08201951,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02394712878592109,"score_gpt":0.3057174924526083,"score_spread":0.2817703636666872,"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."}}