{"id":"W1605166609","doi":"10.5751/es-01811-110150","title":"Generating and Fostering Novelty","year":2006,"lang":"en","type":"article","venue":"Ecology and Society","topic":"Innovation, Sustainability, Human-Machine Systems","field":"Social Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Surprise; Computer science; Novelty; Simple (philosophy); Class (philosophy); Redundancy (engineering); Risk analysis (engineering); Simplicity; Management science; Operations research; Artificial intelligence; Engineering; Business; Sociology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001093754,0.0000602006,0.0001016343,0.00001222745,0.00124088,0.00005413432,0.00004474428,0.0001281648,0.00002565793],"category_scores_gemma":[0.00009123543,0.00006159764,0.00002746693,0.00009136909,0.0003300906,0.0001157365,0.00007001856,0.00009651373,0.000001049442],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007922883,"about_ca_system_score_gemma":0.000069112,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00174394,"about_ca_topic_score_gemma":0.004624492,"domain_scores_codex":[0.999299,0.0001134286,0.0001473522,0.0001628926,0.00006960004,0.0002076559],"domain_scores_gemma":[0.9996697,0.0001116879,0.00005514955,0.00005582485,0.00008413206,0.00002348226],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00000258387,0.00004846193,0.7046968,0.00008229043,0.00002624492,0.000002468287,0.05935248,0.00007065431,0.0008517163,0.2246418,0.008563171,0.001661292],"study_design_scores_gemma":[0.0007872286,0.00007323642,0.8899926,0.000009319951,0.00001935184,0.000008081687,0.04428425,0.002290783,0.00005322026,0.03222169,0.02987611,0.000384159],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9884444,0.0001384085,0.0002214143,0.0008548658,0.0002168611,0.0001567017,0.000001192276,0.00004304467,0.009923092],"genre_scores_gemma":[0.9973698,0.00001768909,0.000853783,0.0003204225,0.00046205,0.00001147116,0.000003413482,0.000004390921,0.0009569853],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1924201,"threshold_uncertainty_score":0.954397,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01762514271154663,"score_gpt":0.3003653302923902,"score_spread":0.2827401875808435,"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."}}