{"id":"W2753671137","doi":"10.5210/fm.v22i9.6847","title":"Information <em>in</em> the ecosystem: Against the “information ecosystem”","year":2017,"lang":"en","type":"article","venue":"First Monday","topic":"Innovation, Sustainability, Human-Machine Systems","field":"Social Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Metaphor; Ecosystem; Total human ecosystem; Field (mathematics); Set (abstract data type); Computer science; Sociology; Data science; Ecosystem services; Ecology; World Wide Web; Ecosystem health; Biology; Philosophy","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":"codex-gemma-dda1882f352a","candidate_categories":["sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.008600776,0.0003219626,0.0003765456,0.0002885709,0.006431761,0.002455203,0.00244345,0.0002755326,0.0001054001],"category_scores_gemma":[0.004195869,0.0002141922,0.0001714306,0.0005796924,0.0002142588,0.005951377,0.0003352962,0.0003964766,0.0007291508],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001053292,"about_ca_system_score_gemma":0.0004830067,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002093338,"about_ca_topic_score_gemma":0.03988039,"domain_scores_codex":[0.9957244,0.0006322408,0.001359894,0.0002239424,0.001323749,0.0007357287],"domain_scores_gemma":[0.9951007,0.0003421638,0.001455314,0.001939398,0.001062016,0.0001003688],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003992891,0.00006168139,0.01202179,0.000730997,0.00006154288,0.000003218553,0.8740368,0.001975628,0.000006446122,0.06734946,0.03526882,0.008443601],"study_design_scores_gemma":[0.0005203675,0.00002959579,0.03411882,0.000138098,0.00001544241,0.000002984516,0.02968498,0.004847866,0.000009478503,0.0008349367,0.9294969,0.0003005592],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9149719,0.00007162039,0.0003439417,0.01083907,0.003191538,0.003244329,0.0001259197,0.0002153178,0.06699631],"genre_scores_gemma":[0.9976618,0.00002921647,0.00001917852,0.0003364072,0.0007090174,0.0003327117,0.0001119418,0.00001893827,0.0007808295],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.894228,"threshold_uncertainty_score":0.9985803,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01290194890974634,"score_gpt":0.2660179904389543,"score_spread":0.253116041529208,"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."}}